. set more off

. pwd
/Users/robertyaffee/Documents/data/research/chwk/phase3/Htests/H1tests/H1pt1/work

. di c(filename)
chwide26june2012.dta

. di "$User"


.
. cd /Users/robertyaffee/Documents/data/research/chwk/phase3/Htests/H1tests/H1pt1/work
/Users/robertyaffee/Documents/data/research/chwk/phase3/Htests/H1tests/H1pt1/work

. use chwide25june2012, clear
(Zero for missing on all icdx)

. save chwide26june2012, replace
file chwide26june2012.dta saved

.
. di c(machine_type)
Macintosh (Intel 64-bit)

. di c(os)
MacOSX

. di c(osdtl)
10.6.8

.
.
.
. title "Hypothesis 1 part 1  Male Dose => Energy Level Analysis"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****      Hypothesis 1 part 1  Male Dose => Energy Level Analysis        *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:05  *****
*******************************************************************************
*******************************************************************************


.
.
.
. ***   male basis functions ( most interactions get deleted owing to collinearity)
.
.
.  cap gen bfmEL1 = max(0, BSIsoma - 21928)

.  cap gen bfmEL2 = max(0, 21928 - BSIsoma)

.  cap gen bfmEL3 = max(0, BSIposymp - 21988)

.  cap gen bfmEL4 = max(0, 21988 - BSIposymp)

.  cap gen bfmEL6 = max(0, 21921 - suprtw2) * bfmEL3

.  cap gen bfmEL7 = max(0, age - 46) * bfmEL1

.  cap gen bfmEL8 = max(0, 46 - age) * bfmEL1

.  cap gen bfmEL9 = max(0, avgcumdosew3 - 21916) * bfmEL2

.  cap gen bfmEL10 = max(0, drinkspww2 - 21916.3) * bfmEL1

.  cap gen bfmEL11 = max(0, 21916.3 - drinkspww2) * bfmEL1

.  cap gen bfmEL12 = max(0, BSIpar - 21926) * bfmEL3

.  cap gen bfmEL13 = max(0, 21926 - BSIpar) * bfmEL3

.  cap gen bfmEL14 = max(0, occ5w3 - 21916) * bfmEL3

.  cap gen bfmEL16 = max(0, 22136 - kmacc)

.  cap gen bfmEL17 = max(0, depagw1 - 21976) * bfmEL16

.  cap gen bfmEL18 = max(0, 21976 - depagw1) * bfmEL16

.
.  label var bfmEL1 " max(0, BSIsoma - 21928)"

.  label var bfmEL2 " max(0, 21928 - BSIsoma)"

.  label var bfmEL3 " max(0, BSIposymp - 21988)"

.  label var bfmEL4 " max(0, 21988 - BSIposymp)"

.  label var bfmEL6 " max(0, 21921 - suprtw2) * bfmEL3"

.  label var bfmEL7 " max(0, age - 46) * bfmEL1 "

.  label var bfmEL8 " max(0, 46 - age) * bfmEL1"

.  label var bfmEL9 " max(0, avgcumdosew3 - 21916) * bfmEL2"

.  label var bfmEL10 " max(0, drinkspww2 - 21916.3) * bfmEL1"

.  label var bfmEL11 " max(0, 21916.3 - drinkspww2) * bfmEL1"

.  label var bfmEL12 " max(0, BSIpar - 21926) * bfmEL3"

.  label var bfmEL13 " max(0, 21926 - BSIpar) * bfmEL3"

.  label var bfmEL14 " max(0, occ5w3 - 21916) * bfmEL3"

.  label var bfmEL16 " max(0, 22136 - kmacc)"

.  label var bfmEL17 " max(0, depagw1 - 21976) * bfmEL16"

.  label var bfmEL18 " max(0, 21976 - depagw1) * bfmEL16"

.
.
.
. title "Wave one male full dose energy level response model"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****        Wave one male full dose energy level response model          *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:05  *****
*******************************************************************************
*******************************************************************************


.
.
. set more off

. des WHPel age educ2-educ7 marrw11-marrw13 marrw15 childw1 ///
>   emplw12-emplw16 occ1w1-occ8w1 inc1w1-inc4w1 radhlw1 radchw1 ///
>   radtlw1 havmil bfmEL2 bfmEL4 bfmEL16 ///
>      dvcew1 sepaw1 ///
>     shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 healthef carcin  ///
>     dafter near chsize  icdxcnt

              storage  display     value
variable name   type   format      label      variable label
-------------


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


age               byte     %8.0g                    *   Respondent's age


educ2             byte     %8.0g                        educ==2. graduated high school


educ3             byte     %8.0g                        educ==3. technical degree


educ4             byte     %8.0g                        educ==4. did not finish college/bachelor's


educ5             byte     %8.0g                        educ==5. graduated college/bachelor's


educ6             byte     %8.0g                        educ==6. finished specialist/master's degree


educ7             byte     %8.0g                        educ==7. doctor of science/phd


marrw11           byte     %8.0g                        marrw1==1. single


marrw12           byte     %8.0g                        marrw1==2. cohabitating


marrw13           byte     %8.0g                        marrw1==3. married


marrw15           byte     %8.0g                        marrw1==5. divorced


childw1           byte     %8.0g                        number of children in 1986


emplw12           byte     %8.0g                        emplw1==1. full time


emplw13           byte     %8.0g                        emplw1==2. part time


emplw14           byte     %8.0g                        emplw1==3. voluntary


emplw15           byte     %8.0g                        emplw1==4. retired


emplw16           byte     %8.0g                        emplw1==5. unemployed


occ1w1            byte     %15.0g        LABJ           profess executive administration in 1986


occ2w1            byte     %15.0g        LABJ           technical sales admin support  in 1986


occ3w1            byte     %15.0g        LABJ           service occup protective services  in 1986


occ4w1            byte     %15.0g        LABJ           precision prod mechan craft construction  in 1986


occ5w1            byte     %15.0g        LABJ           factory laborer machinist transp cleaner  in 1986


occ6w1            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging  in 1986


occ7w1            byte     %15.0g        LABJ           homemaking or caregiving  in 1986


occ8w1            byte     %15.0g        LABJ           student  in 1986


inc1w1            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities in 1986


inc2w1            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities in 1986


inc3w1            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings in 1986


inc4w1            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items in 1986


radhlw1           byte     %8.0g                        Self-perceived Chornobyl health threat in wave 1


radchw1           byte     %8.0g                        believed % of polution related to chornobyl in 1986


radtlw1           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime in 1986


havmil            double   %9.0g                        Distance from Chornobyl in miles


bfmEL2            float    %9.0g                         max(0, 21928 - BSIsoma)


bfmEL4            float    %9.0g                         max(0, 21988 - BSIposymp)


bfmEL16           float    %9.0g                         max(0, 22136 - kmacc)


dvcew1            byte     %8.0g                        Total number of divorces experienced in time period 1976-1986


sepaw1            byte     %8.0g                        Total number of separations experienced in time period 1976-1986


shhlw1            byte     %8.0g                        Percentage of strains and hassles related to health in 1986


shhousw1          byte     %8.0g                        Percentage of strains and hassles related to housing in 1986


phlthw1           byte     %8.0g                        level of general physical health in 1986


suprtw1           byte     %8.0g                        Level of support (in percent) from partner in 1986


fdferw1           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 197


healthef          byte     %8.0g                    *   a person exposed to any radiation  likely to suffer from (% of agreement)


carcin            byte     %8.0g                    *   a person exposed to carcinogen  is likely to get cancer (% of agreement)


dafter            int      %8.0g                    *   how many days lapsed after Chornobyl accident before you heard about the acciden


near              byte     %8.0g                    *   radiation from a nuclear plant site is more concentrated near the plant (% of ag


chsize            byte     %8.0g                    *   the radioactive fallout from chornobyl affected more people than the radioactive


icdxcnt           byte     %9.0g                        count of icdx illnesses


.
. regress WHPel age educ2-educ7 marrw11-marrw13 marrw15 childw1 ///
>   emplw12-emplw16 occ1w1-occ8w1 inc1w1-inc4w1 radhlw1 radchw1 ///
>   radtlw1 havmil bfmEL2 bfmEL4 bfmEL16 dvcew1 sepaw1 ///
>    shhlw1 shhousw1 phlthw1 healthef suprtw1 fdferw1 carcin ///
>    dafter near chsize polprw1 icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     336
                                                       F( 48,   335) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4722
                                                       Root MSE      =  23.659

(Std. Err. adjusted for 336 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .5162134    .2545085      2.03    0.043      .0155772      1.01685
       educ2 |    25.76872    15.99624      1.61    0.108     -5.697023     57.23446
       educ3 |    24.85643    15.17597      1.64    0.102      -4.99578     54.70864
       educ4 |    19.61361    15.44909      1.27    0.205     -10.77583     50.00306
       educ5 |    28.09557    15.38404      1.83    0.069     -2.165933     58.35707
       educ6 |    25.35583    15.22782      1.67    0.097     -4.598374     55.31002
       educ7 |    28.01753    18.89924      1.48    0.139     -9.158611     65.19367
     marrw11 |    .5742487    6.729163      0.09    0.932     -12.66249     13.81099
     marrw12 |   -34.30995    12.50599     -2.74    0.006     -58.91011    -9.709789
     marrw13 |   -12.83407    8.637278     -1.49    0.138      -29.8242      4.15607
     marrw15 |    22.34065    16.57452      1.35    0.179      -10.2626      54.9439
     childw1 |    2.462458    2.877025      0.86    0.393     -3.196853     8.121769
     emplw12 |    -.909535    12.31592     -0.07    0.941     -25.13582     23.31675
     emplw13 |   -4.550379    12.28223     -0.37    0.711     -28.71039     19.60964
     emplw14 |    11.79167    16.91123      0.70    0.486     -21.47391     45.05725
     emplw15 |   -1.847638    20.76961     -0.09    0.929     -42.70293     39.00765
     emplw16 |    -.901729    13.02973     -0.07    0.945     -26.53212     24.72867
      occ1w1 |    6.684843    10.93863      0.61    0.542     -14.83222     28.20191
      occ2w1 |   -7.544009    11.27717     -0.67    0.504       -29.727     14.63898
      occ3w1 |     6.47608    13.21652      0.49    0.624     -19.52175     32.47391
      occ4w1 |   -7.266231    11.61562     -0.63    0.532     -30.11498     15.58252
      occ5w1 |    6.944963    12.55709      0.55    0.581     -17.75572     31.64565
      occ6w1 |     6.70162    12.04366      0.56    0.578     -16.98911     30.39235
      occ7w1 |   -21.18552    14.24555     -1.49    0.138     -49.20751     6.836478
      occ8w1 |    3.836964     11.5262      0.33    0.739     -18.83588     26.50981
      inc1w1 |     4.75152    8.609246      0.55    0.581     -12.18347     21.68652
      inc2w1 |    2.772664    8.500158      0.33    0.744     -13.94775     19.49307
      inc3w1 |    8.433738    8.688364      0.97    0.332     -8.656889     25.52436
      inc4w1 |     9.20006    9.474118      0.97    0.332     -9.436199     27.83632
     radhlw1 |   -.0183632    .0577252     -0.32    0.751     -.1319127     .0951863
     radchw1 |    -.000903    .0530033     -0.02    0.986     -.1051643     .1033582
     radtlw1 |    .0976357    .0554023      1.76    0.079     -.0113446      .206616
      havmil |    .0368408    .0295072      1.25    0.213     -.0212019     .0948836
      bfmEL2 |   -1.373308    .5233468     -2.62    0.009     -2.402768    -.3438477
      bfmEL4 |   -.3825732    .1229447     -3.11    0.002     -.6244141    -.1407323
     bfmEL16 |    .0308178    .0184627      1.67    0.096     -.0054997     .0671353
      dvcew1 |   -47.52869     14.1357     -3.36    0.001     -75.33461    -19.72277
      sepaw1 |    31.96713    12.11308      2.64    0.009      8.139841     55.79442
      shhlw1 |   -.1413466    .0649582     -2.18    0.030     -.2691239    -.0135692
    shhousw1 |    .1221033    .0617326      1.98    0.049      .0006709     .2435356
     phlthw1 |   -.2503417    .1121567     -2.23    0.026     -.4709617    -.0297216
    healthef |    .6547828    .1541091      4.25    0.000      .3516394     .9579263
     suprtw1 |    .0132266    .0757383      0.17    0.861      -.135756     .1622091
     fdferw1 |    .0857284    .0556953      1.54    0.125     -.0238282      .195285
      carcin |   -.7184811    .1351351     -5.32    0.000     -.9843015    -.4526608
      dafter |    .0160235    .0127859      1.25    0.211     -.0091272     .0411743
        near |   -.1438832    .0430021     -3.35    0.001     -.2284715     -.059295
      chsize |   -.1256324      .05382     -2.33    0.020     -.2315002    -.0197646
     polprw1 |   -.0823268    .0443393     -1.86    0.064     -.1695453     .0048917
     icdxcnt |    3.395729    1.045264      3.25    0.001      1.339621     5.451837
       _cons |    37812.88    9939.474      3.80    0.000      18261.24     57364.53
-------------+----------------------------------------------------------------

.
. scalar fw1 = e(r2_a)

. *  R^2 for full model wave 1
.
. title "wave 1 trimmed male model with basis functions"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****           wave 1 trimmed male model with basis functions            *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:05  *****
*******************************************************************************
*******************************************************************************


.
. set more off

. des WHPel age educ2-educ7 marrw11-marrw13 marrw15 childw1 ///
>   emplw12-emplw16 occ1w1-occ8w1 inc1w1-inc4w1 radhlw1 radchw1 ///
>   radtlw1 havmil bfmEL2 bfmEL4 bfmEL16

              storage  display     value
variable name   type   format      label      variable label
-------------


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


age               byte     %8.0g                    *   Respondent's age


educ2             byte     %8.0g                        educ==2. graduated high school


educ3             byte     %8.0g                        educ==3. technical degree


educ4             byte     %8.0g                        educ==4. did not finish college/bachelor's


educ5             byte     %8.0g                        educ==5. graduated college/bachelor's


educ6             byte     %8.0g                        educ==6. finished specialist/master's degree


educ7             byte     %8.0g                        educ==7. doctor of science/phd


marrw11           byte     %8.0g                        marrw1==1. single


marrw12           byte     %8.0g                        marrw1==2. cohabitating


marrw13           byte     %8.0g                        marrw1==3. married


marrw15           byte     %8.0g                        marrw1==5. divorced


childw1           byte     %8.0g                        number of children in 1986


emplw12           byte     %8.0g                        emplw1==1. full time


emplw13           byte     %8.0g                        emplw1==2. part time


emplw14           byte     %8.0g                        emplw1==3. voluntary


emplw15           byte     %8.0g                        emplw1==4. retired


emplw16           byte     %8.0g                        emplw1==5. unemployed


occ1w1            byte     %15.0g        LABJ           profess executive administration in 1986


occ2w1            byte     %15.0g        LABJ           technical sales admin support  in 1986


occ3w1            byte     %15.0g        LABJ           service occup protective services  in 1986


occ4w1            byte     %15.0g        LABJ           precision prod mechan craft construction  in 1986


occ5w1            byte     %15.0g        LABJ           factory laborer machinist transp cleaner  in 1986


occ6w1            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging  in 1986


occ7w1            byte     %15.0g        LABJ           homemaking or caregiving  in 1986


occ8w1            byte     %15.0g        LABJ           student  in 1986


inc1w1            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities in 1986


inc2w1            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities in 1986


inc3w1            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings in 1986


inc4w1            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items in 1986


radhlw1           byte     %8.0g                        Self-perceived Chornobyl health threat in wave 1


radchw1           byte     %8.0g                        believed % of polution related to chornobyl in 1986


radtlw1           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime in 1986


havmil            double   %9.0g                        Distance from Chornobyl in miles


bfmEL2            float    %9.0g                         max(0, 21928 - BSIsoma)


bfmEL4            float    %9.0g                         max(0, 21988 - BSIposymp)


bfmEL16           float    %9.0g                         max(0, 22136 - kmacc)


.
.
. // trimming the model with backward elimination
. set more off

. sw,pr(.1): regress WHPel age educ2-educ7 marrw11-marrw13 marrw15 childw1 ///
>   emplw12-emplw16 occ1w1-occ8w1 inc1w1-inc4w1 radhlw1 radchw1 carcin healthef ///
>   radtlw1 havmil bfmEL2 bfmEL4 bfmEL16 dvcew1 sepaw1 ///
>    shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 ///
>    dafter near chsize polprw1 icdxcnt if gender==1, vce(cluster id)


  begin with full model


p = 0.9864 >= 0.1000  removing radchw1


p = 0.9437 >= 0.1000  removing emplw16


p = 0.9994 >= 0.1000  removing marrw11


p = 0.9961 >= 0.1000  removing emplw12


p = 0.9391 >= 0.1000  removing emplw15


p = 0.8609 >= 0.1000  removing suprtw1


p = 0.7726 >= 0.1000  removing inc2w1


p = 0.7350 >= 0.1000  removing radhlw1


p = 0.6178 >= 0.1000  removing inc1w1


p = 0.4698 >= 0.1000  removing occ4w1


p = 0.6234 >= 0.1000  removing occ2w1


p = 0.3158 >= 0.1000  removing inc4w1


p = 0.2781 >= 0.1000  removing childw1


p = 0.2570 >= 0.1000  removing inc3w1


p = 0.2180 >= 0.1000  removing marrw15


p = 0.2100 >= 0.1000  removing emplw13


p = 0.1987 >= 0.1000  removing havmil


p = 0.1824 >= 0.1000  removing bfmEL16


p = 0.1993 >= 0.1000  removing dafter


p = 0.1589 >= 0.1000  removing occ3w1


p = 0.2619 >= 0.1000  removing emplw14


p = 0.1700 >= 0.1000  removing occ5w1


p = 0.1984 >= 0.1000  removing occ8w1


p = 0.1791 >= 0.1000  removing educ4


p = 0.2917 >= 0.1000  removing educ7


p = 0.2143 >= 0.1000  removing educ3


p = 0.4344 >= 0.1000  removing educ6


p = 0.5175 >= 0.1000  removing educ5


p = 0.3609 >= 0.1000  removing educ2


Linear regression                                      Number of obs =     336
                                                       F( 21,   335) =   18.00
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4312
                                                       Root MSE      =    23.4

(Std. Err. adjusted for 336 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .4850337    .1718245      2.82    0.005      .1470428     .8230246
      dvcew1 |   -30.68434    16.10553     -1.91    0.058     -62.36504     .9963689
      bfmEL4 |   -.3728317     .112517     -3.31    0.001     -.5941606    -.1515029
     fdferw1 |    .1050531    .0484238      2.17    0.031      .0098001      .200306
      occ6w1 |    8.675087    3.853692      2.25    0.025      1.094603     16.25557
      occ7w1 |   -21.85571     6.84426     -3.19    0.002     -35.31885    -8.392562
    shhousw1 |    .1201482     .053549      2.24    0.026      .0148135     .2254829
      chsize |   -.1293454    .0513235     -2.52    0.012     -.2303022    -.0283885
     marrw12 |   -33.90136      8.8596     -3.83    0.000     -51.32882     -16.4739
     marrw13 |   -13.36534    4.328789     -3.09    0.002     -21.88038     -4.85031
      bfmEL2 |   -1.397565    .4684157     -2.98    0.003     -2.318972    -.4761584
    healthef |    .6228537    .1326379      4.70    0.000      .3619455     .8837619
        near |   -.1381138     .038786     -3.56    0.000     -.2144086    -.0618191
     radtlw1 |    .0792528    .0397767      1.99    0.047      .0010091     .1574964
     phlthw1 |   -.2293904    .1017907     -2.25    0.025     -.4296198    -.0291609
      carcin |     -.71292     .116834     -6.10    0.000     -.9427407    -.4830992
     polprw1 |   -.0741828    .0405388     -1.83    0.068     -.1539255     .0055599
      occ1w1 |    10.85392    3.962436      2.74    0.006      3.059529     18.64831
      sepaw1 |    28.44701      14.973      1.90    0.058     -1.005937     57.89996
     icdxcnt |    3.305419    .9614664      3.44    0.001      1.414147     5.196692
      shhlw1 |   -.1377549     .054491     -2.53    0.012     -.2449425    -.0305674
       _cons |    38841.64    8777.807      4.42    0.000      21575.08     56108.21
-------------+----------------------------------------------------------------

.
.
. // Construction of a matrix for scalar storage for each retreival
.
. matrix define MaleWHPelr2 = J(4,7,0)

. matrix colnames MaleWHPelr2 = FullBFR2a TR2aBF  TR2aNoBF  NumBF  BFR2cha NumMods NumMeds

. matrix rownames MaleWHPelr2 = wave1  wave2  wave3  avg

. matlist MaleWHPelr2

   | FullBFR2a    TR2aBF    TR2aNoBF    NumBF    BFR2cha    NumMods    NumMeds
-------------+-----------------------------------------------------------------------------
wave1   |         0            0            0            0            0            0            0
wave2   |         0            0            0            0            0            0            0
wave3   |         0            0            0            0            0            0            0
avg   |         0            0            0            0            0            0            0

.
.
.
. // the proper model after some trimming
.
.
. set more off

. des WHPel age educ2-educ7 marrw11-marrw13 marrw14 marrw15 ///
>      dvcew1 sepaw1 ///
>     shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 healthef carcin  ///
>     dafter near chsize bfmEL4 icdxcnt

              storage  display     value
variable name   type   format      label      variable label
-------------


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


age               byte     %8.0g                    *   Respondent's age


educ2             byte     %8.0g                        educ==2. graduated high school


educ3             byte     %8.0g                        educ==3. technical degree


educ4             byte     %8.0g                        educ==4. did not finish college/bachelor's


educ5             byte     %8.0g                        educ==5. graduated college/bachelor's


educ6             byte     %8.0g                        educ==6. finished specialist/master's degree


educ7             byte     %8.0g                        educ==7. doctor of science/phd


marrw11           byte     %8.0g                        marrw1==1. single


marrw12           byte     %8.0g                        marrw1==2. cohabitating


marrw13           byte     %8.0g                        marrw1==3. married


marrw14           byte     %8.0g                        marrw1==4. separated


marrw15           byte     %8.0g                        marrw1==5. divorced


dvcew1            byte     %8.0g                        Total number of divorces experienced in time period 1976-1986


sepaw1            byte     %8.0g                        Total number of separations experienced in time period 1976-1986


shhlw1            byte     %8.0g                        Percentage of strains and hassles related to health in 1986


shhousw1          byte     %8.0g                        Percentage of strains and hassles related to housing in 1986


phlthw1           byte     %8.0g                        level of general physical health in 1986


suprtw1           byte     %8.0g                        Level of support (in percent) from partner in 1986


fdferw1           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 197


healthef          byte     %8.0g                    *   a person exposed to any radiation  likely to suffer from (% of agreement)


carcin            byte     %8.0g                    *   a person exposed to carcinogen  is likely to get cancer (% of agreement)


dafter            int      %8.0g                    *   how many days lapsed after Chornobyl accident before you heard about the acciden


near              byte     %8.0g                    *   radiation from a nuclear plant site is more concentrated near the plant (% of ag


chsize            byte     %8.0g                    *   the radioactive fallout from chornobyl affected more people than the radioactive


bfmEL4            float    %9.0g                         max(0, 21988 - BSIposymp)


icdxcnt           byte     %9.0g                        count of icdx illnesses


. regress WHPel age educ2-educ7 marrw11-marrw13 marrw14 marrw15 ///
>      dvcew1 sepaw1 ///
>     shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 healthef carcin  ///
>     dafter near chsize  bfmEL2 bfmEL4  if gender==1, vce(cluster id)
note: marrw14 omitted because of collinearity

Linear regression                                      Number of obs =     338
                                                       F( 25,   337) =   29.63
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3973
                                                       Root MSE      =  24.249

(Std. Err. adjusted for 338 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .6225083    .1790673      3.48    0.001      .2702778     .9747388
       educ2 |     28.9308    13.55445      2.13    0.034      2.268819     55.59277
       educ3 |    25.05493    12.09582      2.07    0.039      1.262105     48.84776
       educ4 |    16.79728    12.75021      1.32    0.189      -8.28274     41.87731
       educ5 |    29.99367    12.65279      2.37    0.018      5.105274     54.88207
       educ6 |    27.85131    12.22189      2.28    0.023      3.810507     51.89212
       educ7 |    31.40148    16.04314      1.96    0.051     -.1558337      62.9588
     marrw11 |    8.419736    6.466407      1.30    0.194     -4.299869     21.13934
     marrw12 |   -21.62165    9.510355     -2.27    0.024     -40.32878     -2.91451
     marrw13 |   -2.166159    7.746566     -0.28    0.780     -17.40387     13.07156
     marrw14 |           0   (omitted)
     marrw15 |    22.52385    16.92589      1.33    0.184     -10.76985     55.81756
      dvcew1 |   -35.02589    15.25686     -2.30    0.022     -65.03657    -5.015219
      sepaw1 |     29.1634    14.90162      1.96    0.051     -.1485065     58.47531
      shhlw1 |   -.1198894    .0607308     -1.97    0.049     -.2393486    -.0004303
    shhousw1 |    .1252767     .059066      2.12    0.035      .0090922     .2414611
     phlthw1 |   -.2353777    .1045045     -2.25    0.025      -.440941    -.0298144
     suprtw1 |    .0909864    .0547364      1.66    0.097     -.0166816     .1986545
     fdferw1 |    .0740738    .0497859      1.49    0.138     -.0238563      .172004
    healthef |    .5978986    .1440213      4.15    0.000      .3146047     .8811925
      carcin |   -.6772123    .1271662     -5.33    0.000     -.9273518    -.4270727
      dafter |    .0286304    .0096345      2.97    0.003      .0096791     .0475816
        near |   -.1575489    .0439474     -3.58    0.000     -.2439946    -.0711031
      chsize |   -.1361969    .0500852     -2.72    0.007     -.2347159    -.0376779
      bfmEL2 |   -1.118747    .5148503     -2.17    0.030     -2.131472     -.106022
      bfmEL4 |   -.4637021    .1175894     -3.94    0.000     -.6950036    -.2324005
       _cons |    34688.72    9644.698      3.60    0.000      15717.33     53660.12
-------------+----------------------------------------------------------------

.
. scalar tw1bf = e(r2_a)

. scalar list tw1bf
     tw1bf =  .34901196

. scalar list
W2maleELmed = age radfmw3 sleep, illww3 and Hp2sxlife
W2maleELMed = age and hp2sxlife
W1MaleELMed = radhlw1 and depagw1
w1maleELmods = age suprtw1 fdferw1 chsizew1 icdxcnt
w1numbmaleELmods =          5
w1numaleElmods =          5
 r2chabfw1 =  .07938894
     twbf2 =  .48490811
    twnobf =  .26459544
FemPainDoseMedsw3 = age illw3 phlthw3 radfmw3 hospw3 and radhlw3
    badout =          0
    ckcrit =  .31764707
  pctvalid =       62.5
pctinvalid =       37.5
 numMedFw2 =          1
FemPainW2Med = age
numbfsigfw2 =          9
   dsigfw2 =          0
       fw2 =  .57745936
FemPainW1Meds = educ and age
numModsigFw1 =          0
numbfsigfw1 =          1
numMainEffsigFw1 =          5
   dsigfw1 =          0
numMedPainDoseFsigw3 =          6
numbfsigTw3 =         15
numModsigTw3 =          0
numModsigFw3 =          0
numbfsigfw3 =         15
   dsigtw3 =          0
 numMedFw3 =         15
numMainEffsigTw3 =         16
   dsigfw3 =          0
numMainEffsigFw3 =         16
       fw3 =  .63678289
numbfsigtw2 =          0
 numMedMw2 =          2
   w2numbf =          7
numbfsigTw2 =          9
   tw2nobf =  .26459544
numModsigTw2 =          3
     tw2bf =  .29409811
numMainEffsigTw2 =          5
   dsigtw2 =          0
numbfsigMw2 =          0
numModsigFw2 =          2
numbfsigFw2 =          3
numMainEffsigFw2 =          8
   dsigFw2 =         .5
       mw2 =  .35574302
numModsigTw1 =          1
numMainEffsigTw1 =          5
numModsigMw1 =          0
   dsigtw1 =          3
numbfsigtw1 =          2
NumMainEffsigTw1 =         11
numbfsigMw1 =          1
numMainEffsigMw1 =          7
       Mw1 =  .28222811
   dsigMw1 =          1
        wv =          3
        pt =          1
       hyp =          1
W2FemaleELmed = age radfmw3 BSIanx BSIdep icdxcnt radhlw3 illw3 and Hp2sxlife
 numMedsw3 =          4
 numModsw3 =          1
  avgImpBF = -.01588267
 r2chabfw3 = -.04764801
   w3numbf =          3
   tw3bfw3 =  .39169032
W2FemaleELMed = age and radfmw2 radhlw2 radchw2 illw2 BSIanx BSIdep icdxcnt hp2sxlife
   tw3nobf =  .39169032
     tw3bf =  .34404231
    fw3wbf =  .33260096
 numMedsw2 =          2
   tw2bfw2 =  .48481206
avgImpBFw2 =  .07519191
 r2chabfw2 =  .22557574
 NumMedsw2 =          2
 numModsw2 =          0
 w2numbfw2 =          3
 tw2nobfw2 =   .1308152
  tw2wbfw2 =  .35639094
  fw2wbfw2 =  .34555619
W1numMELMeds =          2
W1FemaleELMed = age icdxcnt BSIdep depagw1 BSIanx anxagw1 PTSDw1 HP2sxlife
w1numMElMeds =          2
w1nuFemaleElmods =          0
avgImpBFw1 =  .05367898
   w1numbf =          3
   r2chabf =  .16103694
   tw1nobf =  .18797502
     tw1bf =  .34901196
       fw1 =  .37964479

.
. * tw1bf  r2 for trimmed model with basis functions
.
. set more off

. sw,pr(.1): regress WHPel age educ2-educ7 marrw11-marrw15  ///
>   dvcew1 sepaw1 illw1 shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 ///
>    dafter near chsize  ///
>    icdxcnt trgovw1 carcin ///
>    radhlw1 radchw1 ///
>   radtlw1 havmil if gender==1, vce(cluster id)
note: marrw14 dropped because of collinearity


  begin with full model


p = 0.9267 >= 0.1000  removing radtlw1


p = 0.9215 >= 0.1000  removing radchw1


p = 0.8822 >= 0.1000  removing illw1


p = 0.8498 >= 0.1000  removing marrw15


p = 0.9494 >= 0.1000  removing marrw11


p = 0.7983 >= 0.1000  removing havmil


p = 0.7793 >= 0.1000  removing dafter


p = 0.6445 >= 0.1000  removing shhlw1


p = 0.5500 >= 0.1000  removing trgovw1


p = 0.4422 >= 0.1000  removing shhousw1


p = 0.4025 >= 0.1000  removing sepaw1


p = 0.2794 >= 0.1000  removing carcin


p = 0.2354 >= 0.1000  removing radhlw1


p = 0.1347 >= 0.1000  removing near


p = 0.1413 >= 0.1000  removing dvcew1


p = 0.1691 >= 0.1000  removing marrw13


Linear regression                                      Number of obs =     304
                                                       F( 13,   303) =   11.18
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2228
                                                       Root MSE      =  27.194

(Std. Err. adjusted for 304 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .4095855    .1562839      2.62    0.009      .1020463     .7171246
       educ2 |    24.53598     9.99727      2.45    0.015      4.863112     44.20885
       educ3 |    23.69889    7.545293      3.14    0.002       8.85108      38.5467
       educ4 |    20.58511    10.17503      2.02    0.044      .5624367     40.60778
       educ5 |    22.51775    8.948612      2.52    0.012      4.908452     40.12704
       educ6 |    24.33838     7.61613      3.20    0.002       9.35118     39.32559
       educ7 |    28.26003    12.57952      2.25    0.025      3.505761     53.01431
     suprtw1 |    .3752801    .1998424      1.88    0.061     -.0179746     .7685349
     marrw12 |   -34.82776    4.581693     -7.60    0.000     -43.84373     -25.8118
     icdxcnt |    3.993819     1.13171      3.53    0.000      1.766813     6.220824
     phlthw1 |   -.2039021    .1129959     -1.80    0.072     -.4262582      .018454
      chsize |    -.114942    .0628039     -1.83    0.068     -.2385291     .0086451
     fdferw1 |    .1584967    .0472137      3.36    0.001      .0655885      .251405
       _cons |   -6.616984     15.5485     -0.43    0.671      -37.2137     23.97973
-------------+----------------------------------------------------------------

. eret list

scalars:
            e(N_clust) =  304
                  e(N) =  304
               e(df_m) =  13
               e(df_r) =  303
                  e(F) =  11.17521775258462
                 e(r2) =  .222814372851793
               e(rmse) =  27.19369367097382
                e(mss) =  61482.68731085182
                e(rss) =  214454.1228865208
               e(r2_a) =  .1879750171520458
                 e(ll) =  -1428.298472984467
               e(ll_0) =  -1466.614033309275
               e(rank) =  14

macros:
            e(cmdline) : "stepwise ,pr(.1): regress WHPel age educ2-educ7 marrw11-marrw15    dvcew1 sepaw1 illw1 shhlw1 shhousw1 phlthw1.."
           e(stepwise) : "stepwise"
              e(title) : "Linear regression"
          e(marginsok) : "XB default"
                e(vce) : "cluster"
             e(depvar) : "WHPel"
                e(cmd) : "regress"
         e(properties) : "b V"
            e(predict) : "regres_p"
              e(model) : "ols"
          e(estat_cmd) : "regress_estat"
            e(vcetype) : "Robust"
           e(clustvar) : "id"

matrices:
                  e(b) :  1 x 14
                  e(V) :  14 x 14
       e(V_modelbased) :  14 x 14

functions:
             e(sample)

.
. scalar tw1nobf = e(r2_a)

.
. // r2 for trimmed model without basis functions = .183
.
. scalar w1numbf= 3

.
. scalar avgImpBFw1 = r2chabf/w1numbf

. * avgImpBF = average improvement per basis function
.
. scalar r2chabf = tw1bf-tw1nobf

. * R^ change due to basis functions
. scalar list
W2maleELmed = age radfmw3 sleep, illww3 and Hp2sxlife
W2maleELMed = age and hp2sxlife
W1MaleELMed = radhlw1 and depagw1
w1maleELmods = age suprtw1 fdferw1 chsizew1 icdxcnt
w1numbmaleELmods =          5
w1numaleElmods =          5
 r2chabfw1 =  .07938894
     twbf2 =  .48490811
    twnobf =  .26459544
FemPainDoseMedsw3 = age illw3 phlthw3 radfmw3 hospw3 and radhlw3
    badout =          0
    ckcrit =  .31764707
  pctvalid =       62.5
pctinvalid =       37.5
 numMedFw2 =          1
FemPainW2Med = age
numbfsigfw2 =          9
   dsigfw2 =          0
       fw2 =  .57745936
FemPainW1Meds = educ and age
numModsigFw1 =          0
numbfsigfw1 =          1
numMainEffsigFw1 =          5
   dsigfw1 =          0
numMedPainDoseFsigw3 =          6
numbfsigTw3 =         15
numModsigTw3 =          0
numModsigFw3 =          0
numbfsigfw3 =         15
   dsigtw3 =          0
 numMedFw3 =         15
numMainEffsigTw3 =         16
   dsigfw3 =          0
numMainEffsigFw3 =         16
       fw3 =  .63678289
numbfsigtw2 =          0
 numMedMw2 =          2
   w2numbf =          7
numbfsigTw2 =          9
   tw2nobf =  .26459544
numModsigTw2 =          3
     tw2bf =  .29409811
numMainEffsigTw2 =          5
   dsigtw2 =          0
numbfsigMw2 =          0
numModsigFw2 =          2
numbfsigFw2 =          3
numMainEffsigFw2 =          8
   dsigFw2 =         .5
       mw2 =  .35574302
numModsigTw1 =          1
numMainEffsigTw1 =          5
numModsigMw1 =          0
   dsigtw1 =          3
numbfsigtw1 =          2
NumMainEffsigTw1 =         11
numbfsigMw1 =          1
numMainEffsigMw1 =          7
       Mw1 =  .28222811
   dsigMw1 =          1
        wv =          3
        pt =          1
       hyp =          1
W2FemaleELmed = age radfmw3 BSIanx BSIdep icdxcnt radhlw3 illw3 and Hp2sxlife
 numMedsw3 =          4
 numModsw3 =          1
  avgImpBF = -.01588267
 r2chabfw3 = -.04764801
   w3numbf =          3
   tw3bfw3 =  .39169032
W2FemaleELMed = age and radfmw2 radhlw2 radchw2 illw2 BSIanx BSIdep icdxcnt hp2sxlife
   tw3nobf =  .39169032
     tw3bf =  .34404231
    fw3wbf =  .33260096
 numMedsw2 =          2
   tw2bfw2 =  .48481206
avgImpBFw2 =  .07519191
 r2chabfw2 =  .22557574
 NumMedsw2 =          2
 numModsw2 =          0
 w2numbfw2 =          3
 tw2nobfw2 =   .1308152
  tw2wbfw2 =  .35639094
  fw2wbfw2 =  .34555619
W1numMELMeds =          2
W1FemaleELMed = age icdxcnt BSIdep depagw1 BSIanx anxagw1 PTSDw1 HP2sxlife
w1numMElMeds =          2
w1nuFemaleElmods =          0
avgImpBFw1 =  .05367898
   w1numbf =          3
   r2chabf =  .16103694
   tw1nobf =  .18797502
     tw1bf =  .34901196
       fw1 =  .37964479

.
. scalar w1numaleElmods=5

. scalar w1numMElMeds=2

. *
. matrix define MaleWHPelr2w1 = (fw1, tw1bf, tw1nobf, w1numbf,  r2chabf, avgImpBFw1, w1numaleElmods, w1numMElMeds)

. matrix colnames MaleWHPelr2w1 = FullBFR2a TR2aBF  TR2aNoBF  NumBF  BFR2cha  AvgImpBF  w1numMods w1numMeds

. matrix rownames MaleWHPelr2w1 = wave1

. matlist MaleWHPelr2w1

   | FullBFR2a    TR2aBF    TR2aNoBF    NumBF    BFR2cha    AvgImpBF    w1numMods    w1numMeds
-------------+----------------------------------------------------------------------------------------
wave1   |  .3796448      .349012      .187975            3     .1610369      .053679            5            2

. ********************************************************************************
.
. title2 "Wave 1 male moderation analysis"
-------------
title2: Wave 1 male moderation analysis
                                       Date and time:  29 Jun 2012    07:48:09
                                       Working directory:  /Users/robertyaffee/Documents/data/research/chwk/phase3/Htests/H1tests/H1pt1/work
                                       Stata data file:  chwide26june2012.dta  has  4175  variables and  703  observations

Wave 1 male moderation analysis
-------------

.
. foreach var in  suprtw1 fdferw1 chsize icdxcnt {
  2.  cap  gen `var'Xd1 = `var'* avgcumdosew1
  3.     }

.
. regress WHPel age educ2-educ7 marrw11-marrw13 marrw14 marrw15 ///
>      dvcew1 sepaw1 ///
>     shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 healthef carcin  ///
>     dafter near chsize  bfmEL2 bfmEL4 bfmEL16 ///
>     ageXd1 suprtw1Xd1 fdferw1Xd1 chsizeXd1 icdxcntXd1 if gender==1, vce(cluster id)
note: marrw14 omitted because of collinearity

Linear regression                                      Number of obs =     338
                                                       F( 30,   337) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4268
                                                       Root MSE      =  23.879

(Std. Err. adjusted for 338 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .7376643    .1874361      3.94    0.000      .3689721     1.106356
       educ2 |    28.10889    13.30269      2.11    0.035      1.942128     54.27566
       educ3 |    24.05741    12.01056      2.00    0.046      .4323007     47.68253
       educ4 |    15.89713    12.62816      1.26    0.209     -8.942812     40.73707
       educ5 |     28.2783    12.56512      2.25    0.025      3.562352     52.99425
       educ6 |    26.42372    12.04189      2.19    0.029      2.736981     50.11047
       educ7 |    31.00788    15.37019      2.02    0.044      .7742805     61.24148
     marrw11 |    3.883875    6.056056      0.64    0.522     -8.028559     15.79631
     marrw12 |   -25.95991    9.305342     -2.79    0.006     -44.26378    -7.656039
     marrw13 |   -7.038911      7.4207     -0.95    0.344     -21.63564     7.557817
     marrw14 |           0   (omitted)
     marrw15 |    22.96251    18.70271      1.23    0.220     -13.82625     59.75126
      dvcew1 |   -40.60905    17.55242     -2.31    0.021     -75.13515    -6.082946
      sepaw1 |    33.69141    17.19483      1.96    0.051     -.1313166     67.51413
      shhlw1 |   -.1428862    .0613073     -2.33    0.020     -.2634793     -.022293
    shhousw1 |     .140813    .0604047      2.33    0.020      .0219952     .2596307
     phlthw1 |   -.2017424    .1062757     -1.90    0.059     -.4107897     .0073049
     suprtw1 |    .0135952    .0625843      0.22    0.828     -.1095098     .1367002
     fdferw1 |    .1102547    .0515368      2.14    0.033      .0088804      .211629
    healthef |     .694739    .1529872      4.54    0.000      .3938089     .9956692
      carcin |   -.7484152     .134221     -5.58    0.000     -1.012432    -.4843987
      dafter |    .0135303    .0117663      1.15    0.251     -.0096143      .036675
        near |   -.1551955    .0445537     -3.48    0.001     -.2428339     -.067557
      chsize |   -.2691267    .0615485     -4.37    0.000     -.3901944     -.148059
      bfmEL2 |    -1.22267    .5281965     -2.31    0.021     -2.261647    -.1836924
      bfmEL4 |   -.4459773    .1225822     -3.64    0.000     -.6870999    -.2048546
     bfmEL16 |    .0070384    .0072561      0.97    0.333     -.0072345     .0213113
      ageXd1 |   -.7415959    .2314029     -3.20    0.001     -1.196772    -.2864198
  suprtw1Xd1 |    .3332002     .096762      3.44    0.001      .1428665     .5235338
  fdferw1Xd1 |   -.1789318     .040906     -4.37    0.000      -.259395    -.0984685
   chsizeXd1 |     .493195    .1347934      3.66    0.000      .2280526     .7583374
  icdxcntXd1 |    3.164978    1.290781      2.45    0.015       .625975     5.703981
       _cons |    36427.47    9839.148      3.70    0.000      17073.59     55781.35
-------------+----------------------------------------------------------------

.
. scalar w1numbmaleELmods= 5

. scalar w1maleELmods = "age suprtw1 fdferw1 chsizew1 icdxcnt"

.
. * moderator1 age we will graph dose => male el for 3 different age ranges"
. * we split age into thirds
.
. summ age if gender==1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         age |       340    49.18235    12.22222         30         77

. tab age if gender==1

Respondent' |
      s age |      Freq.     Percent        Cum.
------------+-----------------------------------
         30 |         16        4.71        4.71
         31 |          6        1.76        6.47
         32 |          5        1.47        7.94
         33 |          3        0.88        8.82
         34 |          7        2.06       10.88
         35 |          4        1.18       12.06
         36 |          9        2.65       14.71
         37 |         13        3.82       18.53
         38 |         15        4.41       22.94
         39 |         15        4.41       27.35
         40 |         16        4.71       32.06
         41 |          9        2.65       34.71
         42 |         10        2.94       37.65
         43 |          6        1.76       39.41
         44 |         10        2.94       42.35
         45 |          8        2.35       44.71
         46 |          8        2.35       47.06
         47 |          4        1.18       48.24
         48 |         11        3.24       51.47
         49 |          4        1.18       52.65
         50 |          8        2.35       55.00
         51 |          8        2.35       57.35
         52 |         12        3.53       60.88
         53 |          8        2.35       63.24
         54 |          4        1.18       64.41
         55 |         18        5.29       69.71
         56 |          6        1.76       71.47
         57 |          8        2.35       73.82
         58 |          7        2.06       75.88
         59 |          4        1.18       77.06
         60 |          7        2.06       79.12
         61 |          8        2.35       81.47
         62 |          5        1.47       82.94
         63 |          6        1.76       84.71
         64 |          5        1.47       86.18
         65 |          3        0.88       87.06
         66 |          2        0.59       87.65
         67 |          3        0.88       88.53
         68 |          4        1.18       89.71
         69 |         11        3.24       92.94
         70 |         12        3.53       96.47
         71 |          2        0.59       97.06
         72 |          3        0.88       97.94
         73 |          2        0.59       98.53
         74 |          2        0.59       99.12
         75 |          1        0.29       99.41
         77 |          2        0.59      100.00
------------+-----------------------------------
      Total |        340      100.00

. cap gen middosew1= avgcumdosew1 if gender==1 & age >= 42 & age < 55

. cap gen lowd1  = avgcumdosew1 if gender== 1 & age < 42

. cap gen hid1 = avgcumdosew1 if gender==1 & age >= 55 & age < .

. cap gen youngdosew1 = avgcumdosew1 if age < 42 & gender==1

. cap gen middosew1 = avgcumdosew1 if age >= 42 & age < 55 & gender==1

. cap gen hidosew1 = avgcumdosew1 if age >= 55 & gender==1 & avgcumdosew1 < .

. replace youngdosew1 = avgcumdosew1 if age < 42 & gender==1
(0 real changes made)

. summ youngdosew1 middosew1 hidosew1 if gender==1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
 youngdosew1 |       118    .2034068    .1245227      .0213     1.0225
   middosew1 |       101    .3033228     .205257      .0151     1.8319
    hidosew1 |       121    .7544694    2.765357      .0147    27.9862

.
. twoway lfit WHPel lowd1 || lfit WHPel middosew1 || lfit WHPel hidosew1,  ///
>          yti(energy level)  ///
>    ti(Effect of age by dose on energy level) ///
>    legend(label( 1 "for young men [28-42 yrs] " ) ///
>     label( 2 "for middle aged [43-54 yrs] men") label(3 "for senior men (55+ yrs)") rows(3))  ///
>    xti("Average cumulative wave 1 dose" "of {superscript:137}CS in milliGrays" ) ///
>    lcolor( blue purple red ) lpattern(dash long_dash dash_dot )

.   graph save ELXdosage1.gph, replace
(file ELXdosage1.gph saved)

.   graph export ELXdosage1.eps, replace
(file ELXdosage1.eps written in EPS format)

.
.
.
.  * moderator 2 in wave 1  the support by dose effect on energy level
.
. histogram suprtw1 if gender==1
(bin=18, start=0, width=5.5555556)

. summ suprtw1 if gender==1, detail

     Level of support (in percent) from partner in 1986
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%            0              0
10%            0              0       Obs                 340
25%            0              0       Sum of Wgt.         340

50%            0                      Mean           9.255882
                        Largest       Std. Dev.      26.33171
75%            0            100
90%           23            100       Variance       693.3591
95%          100            100       Skewness       2.890186
99%          100            100       Kurtosis       9.787807

. cap gen lowsuprt = avgcumdosew1 if suprtw1 < 50 & gender==1

. cap gen hisuprt = avgcumdosew1 if suprtw1 >=50 & suprtw1 < . & gender==1

. twoway lfit WHPel lowsuprt || lfit WHPel hisuprt, ti(Wave 1 interaction of Partner by dose) ///
>   lpattern(dash long_dot) lcolor(red blue) ///
>   subtitle(on Energy Level) yti(Energy level) xti(avgcumdose of {superscript:137}CS in milliGrays) ///
>   legend(label(1 "low partner support") label(2 "high partner support"))

. graph save ELSptXDosew1.gph, replace
(file ELSptXDosew1.gph saved)

. graph export ELSptXDosew1.eps, replace
(file ELSptXDosew1.eps written in EPS format)

.
.
. * moderator 3 in wave 1  fear of eating contaminted food by dose on energy level
. summ fdferw1 if gender==1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
     fdferw1 |       340    32.37059    39.08826          0        100

. histogram fdferw1 if gender==1
(bin=18, start=0, width=5.5555556)

. centile fdferw1 if gender==1, centile(33 67)

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
     fdferw1 |      340        33             0               0           0
             |                 67            50              40          60

. cap gen lowfdferdose = avgcumdosew1 if gender==1 & fdferw1 <=50

. cap gen hifdferdose = avgcumdosew1 if gender==1 & fdferw1 > 50 & fdferw1 < .

. twoway lfit WHPel lowfdferdose || lfit WHPel hifdferdose, ///
>   ti(Wave 1 Fear of contaminated food by dose) lpattern(dash longdash) ///
>   color(red blue) ///
>   subtitle(Effect on Energy Level) yti(Energy level) xti(avgcumdose of {superscript:137}CS in milliGrays) ///
>   legend(label(1 "low fear") label(2 "high fear"))

. graph save ELfdfrXDosew1.gph, replace
(file ELfdfrXDosew1.gph saved)

. graph export ELfdfrXDosew1.eps, replace
(file ELfdfrXDosew1.eps written in EPS format)

.
. * moderator 4 in wave 1
. * Chornobyl was the largest or not
.
. summ chsize if gender==1, detail

       the radioactive fallout from chornobyl affected
              more people than the radioactive
-------------------------------------------------------------
      Percentiles      Smallest
 1%            0              0
 5%           10              0
10%           40              0       Obs                 340
25%           50              0       Sum of Wgt.         340

50%           80                      Mean           73.54706
                        Largest       Std. Dev.      28.30607
75%          100            100
90%          100            100       Variance       801.2338
95%          100            100       Skewness       -.818998
99%          100            100       Kurtosis       2.805331

. histogram chsize if gender==1
(bin=18, start=0, width=5.5555556)

. cap gen lowsized1 = avgcumdosew1 if chsize <= 50 & gender==1

. cap gen hisized1 = avgcumdosew1 if chsize > 50 & chsize < . & gender==1

.
. twoway lfit WHPel lowsized1 || lfit WHPel hisized1 , ///
>    title("Belief that Chornobyl was" "the worst nuclear disaster by dose") ///
>    subti(on Energy level) lcolor(red blue) lpattern(longdash solid ) ///
>     xti(average cumulative wave 1 dose of {superscript:137}CS in milliGrays)  ///
>     ytitle(Energy level) ///
>    legend(label(1 "not the worst by dose") label(2 "the worst by dose"))

. graph save ELsizedosew1.gph, replace
(file ELsizedosew1.gph saved)

. graph export Elsizedosew1.eps, replace
(file Elsizedosew1.eps written in EPS format)

.
. summ icdxcnt if gender==1

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
     icdxcnt |       340    2.144118    1.688009          0          8

. centile icdxcnt if gender==1, centile(33 67)

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
     icdxcnt |      340        33             1               1           1
             |                 67             3               2           3

. cap gen lowctdose = avgcumdosew1 if icdxcnt <= 2 & gender==1

. cap gen midctdose = avgcumdosew1 if icdxcnt > 2 & icdxcnt < 4 & gender==1

. cap gen hictdose = avgcumdosew1 if icdxcnt >=4 & icdxcnt < . & gender==1

.
. twoway lfit WHPel lowctdose || lfit WHPel midctdose || lfit WHPel hictdose, ///
>    title("Effect of medically diagnosed illness" "count by dose on male energy level") ///
>      xti(average cumulative wave 1 dose of {superscript:137}CS in milliGrays)  ///
>      ytitle(Energy level) lcolor(red green blue) lpattern(dash longdash_dot solid) ///
>      legend(label(1 "0 to 2 illnesses") label(2 "3-4 illnesses") ///
>      label(3 "over 4 illnesses"))

. graph save ElillctXdosew1.gph, replace
(file ElillctXdosew1.gph saved)

. graph export ELillctXdosew1.eps, replace
(file ELillctXdosew1.eps written in EPS format)

.
.
. forvalues i=1/3 {
  2.  regress WHPel age fdferw`i' goferw`i' injothr radfmw`i' PTSDw`i' BSIsoma BSIanx c.whpsleep##c.avgcumdosew`i' if gender==2
  3.  }

      Source |       SS       df       MS              Number of obs =     363
-------------+------------------------------           F( 11,   351) =   23.02
       Model |  179979.713    11  16361.7921           Prob > F      =  0.0000
    Residual |  249469.835   351   710.74027           R-squared     =  0.4191
-------------+------------------------------           Adj R-squared =  0.4009
       Total |  429449.548   362  1186.32472           Root MSE      =   26.66

--------------------------+----------------------------------------------------------------
                     WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
--------------------------+----------------------------------------------------------------
                      age |    .2430435    .1408266      1.73    0.085     -.0339266     .5200137
                  fdferw1 |    .0527001    .0563689      0.93    0.350     -.0581631     .1635633
                  goferw1 |   -.0482049    .0597142     -0.81    0.420     -.1656476     .0692377
                  injothr |    .4280841    4.105298      0.10    0.917     -7.645993     8.502161
                  radfmw1 |   -.0169632    .0421847     -0.40    0.688     -.0999298     .0660034
                   PTSDw1 |    .0841677    .0457844      1.84    0.067     -.0058786     .1742141
                  BSIsoma |    2.409797    .3608527      6.68    0.000      1.700092     3.119503
                   BSIanx |   -.1319147    .5399846     -0.24    0.807     -1.193927     .9300977
                 whpsleep |    .2704029    .0714632      3.78    0.000      .1298531     .4109528
             avgcumdosew1 |   -6.095006    8.110262     -0.75    0.453     -22.04583     9.855815
                          |
c.whpsleep#c.avgcumdosew1 |    .0944173    .1340982      0.70    0.482     -.1693197     .3581543
                          |
                    _cons |   -19.79531    7.684451     -2.58    0.010     -34.90867    -4.681956
--------------------------+----------------------------------------------------------------

      Source |       SS       df       MS              Number of obs =     362
-------------+------------------------------           F( 11,   350) =   23.14
       Model |  180382.566    11  16398.4151           Prob > F      =  0.0000
    Residual |  248050.593   350   708.71598           R-squared     =  0.4210
-------------+------------------------------           Adj R-squared =  0.4028
       Total |  428433.159   361  1186.79545           Root MSE      =  26.622

--------------------------+----------------------------------------------------------------
                     WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
--------------------------+----------------------------------------------------------------
                      age |    .2402185    .1382789      1.74    0.083     -.0317437     .5121806
                  fdferw2 |    .1642618    .0723932      2.27    0.024      .0218813     .3066422
                  goferw2 |   -.2243842    .1073909     -2.09    0.037     -.4355968    -.0131715
                  injothr |   -1.231933    4.305492     -0.29    0.775     -9.699823     7.235957
                  radfmw2 |    .0235371    .0514247      0.46    0.647     -.0776032     .1246774
                   PTSDw2 |   -.2467097    .1788693     -1.38    0.169     -.5985037     .1050842
                  BSIsoma |    2.550801    .3552992      7.18    0.000      1.852011     3.249591
                   BSIanx |    .0180083    .5159471      0.03    0.972     -.9967384     1.032755
                 whpsleep |    .2938904    .0685683      4.29    0.000      .1590328     .4287481
             avgcumdosew2 |   -.4654934    2.449142     -0.19    0.849     -5.282381     4.351394
                          |
c.whpsleep#c.avgcumdosew2 |    .0104782    .0450578      0.23    0.816     -.0781399     .0990963
                          |
                    _cons |   -23.34136    7.584451     -3.08    0.002     -38.25819    -8.424527
--------------------------+----------------------------------------------------------------

      Source |       SS       df       MS              Number of obs =     363
-------------+------------------------------           F( 11,   351) =   23.43
       Model |   181808.75    11  16528.0682           Prob > F      =  0.0000
    Residual |  247640.798   351  705.529339           R-squared     =  0.4234
-------------+------------------------------           Adj R-squared =  0.4053
       Total |  429449.548   362  1186.32472           Root MSE      =  26.562

--------------------------+----------------------------------------------------------------
                     WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
--------------------------+----------------------------------------------------------------
                      age |    .2039406    .1363892      1.50    0.136     -.0643022     .4721834
                  fdferw3 |    .1670439    .0860776      1.94    0.053     -.0022488     .3363366
                  goferw3 |   -.0620583    .1199124     -0.52    0.605     -.2978955     .1737788
                  injothr |   -1.790628    4.397042     -0.41    0.684     -10.43849     6.857235
                  radfmw3 |    .0543213    .0501371      1.08    0.279     -.0442855     .1529281
                   PTSDw3 |   -.3263064    .1776855     -1.84    0.067     -.6757684     .0231557
                  BSIsoma |    2.552219    .3528046      7.23    0.000      1.858342     3.246095
                   BSIanx |   -.0109415    .5198371     -0.02    0.983     -1.033329     1.011446
                 whpsleep |    .2831926    .0686861      4.12    0.000      .1481046     .4182806
             avgcumdosew3 |   -1.175953    1.835414     -0.64    0.522     -4.785744     2.433839
                          |
c.whpsleep#c.avgcumdosew3 |    .0160144    .0339187      0.47    0.637      -.050695     .0827238
                          |
                    _cons |   -22.08382    7.509853     -2.94    0.003     -36.85379    -7.313847
--------------------------+----------------------------------------------------------------

.
.
. title "Wave 1 male mediation analysis"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****                   Wave 1 male mediation analysis                    *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:20  *****
*******************************************************************************
*******************************************************************************


.
. title "radhlw1 and depression BSIanxiety are possible male mediators of energy level in wave 1"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****radhlw1 and depression BSIanxiety are possible male mediators of energy level in wave 1*****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:20  *****
*******************************************************************************
*******************************************************************************


.
. cap gen whpel = WHPel

. sem(avgcumdosew1->age)(age->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  age whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3613.4772
Iteration 1:   log likelihood = -3613.4772

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3613.4772

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   age <-         |
    avgcumdosew1 |    .6719789    .3955154      1.70    0.089     -.1032171     1.447175
           _cons |    48.89394    .6805861     71.84    0.000      47.56001     50.22786
  ---------------+----------------------------------------------------------------
   whpel <-       |
             age |    .6520247    .1282979      5.08    0.000      .4005655     .9034839
           _cons |   -8.877521    6.501358     -1.37    0.172     -21.61995     3.864907
-----------------+----------------------------------------------------------------
 Variance         |
           e.age |    147.6893    11.32726                    127.0764     171.6459
         e.whpel |    833.5635     63.9314                    717.2235     968.7748
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.51, Prob > chi2 = 0.2185

. sem(avgcumdosew1->illw1)(illw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  illw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -2444.5273
Iteration 1:   log likelihood = -2444.5273

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -2444.5273

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   illw1 <-       |
    avgcumdosew1 |    .0087277    .0122955      0.71    0.478     -.0153711     .0328264
           _cons |    .0962541    .0211576      4.55    0.000       .054786     .1377221
  ---------------+----------------------------------------------------------------
   whpel <-       |
           illw1 |     6.83786    4.279824      1.60    0.110     -1.550442     15.22616
           _cons |     22.5068    1.673741     13.45    0.000      19.22633     25.78727
-----------------+----------------------------------------------------------------
 Variance         |
         e.illw1 |    .1427297    .0109469                     .122809     .1658817
         e.whpel |    890.2012    68.27532                    765.9563       1034.6
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.49, Prob > chi2 = 0.1145

. sem(avgcumdosew1->radchw1)(radchw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radchw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3992.2619
Iteration 1:   log likelihood = -3992.2619

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3992.2619

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radchw1 <-     |
    avgcumdosew1 |   -.8203903    1.162338     -0.71    0.480     -3.098531      1.45775
           _cons |    53.44329    2.000102     26.72    0.000      49.52316     57.36342
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radchw1 |   -.0274045    .0454187     -0.60    0.546     -.1164236     .0616146
           _cons |    24.64553     2.90682      8.48    0.000      18.94826     30.34279
-----------------+----------------------------------------------------------------
 Variance         |
       e.radchw1 |     1275.52    97.82791                    1097.496      1482.42
         e.whpel |    895.9253    68.71433                    770.8815     1041.252
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.60, Prob > chi2 = 0.1070

. sem(avgcumdosew1->radhlw1)(radhlw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radhlw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3995.8851
Iteration 1:   log likelihood = -3995.8851

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3995.8851

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radhlw1 <-     |
    avgcumdosew1 |    2.398285    1.204853      1.99    0.047      .0368169     4.759752
           _cons |    44.66477    2.073259     21.54    0.000      40.60126     48.72828
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radhlw1 |    .1803734    .0425072      4.24    0.000      .0970609     .2636859
           _cons |    14.94858    2.505565      5.97    0.000      10.03777      19.8594
-----------------+----------------------------------------------------------------
 Variance         |
       e.radhlw1 |    1370.535    105.1152                     1179.25     1592.848
         e.whpel |    851.7752    65.32818                    732.8934     989.9407
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.50, Prob > chi2 = 0.2205

. sem(avgcumdosew1->icdxcnt)(icdxcnt->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  icdxcnt whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -2932.7265
Iteration 1:   log likelihood = -2932.7265

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -2932.7265

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   icdxcnt <-     |
    avgcumdosew1 |    .0453656    .0548008      0.83    0.408      -.062042     .1527731
           _cons |    2.124647    .0942989     22.53    0.000      1.939824     2.309469
  ---------------+----------------------------------------------------------------
   whpel <-       |
         icdxcnt |    6.082854    .9053643      6.72    0.000      4.308372     7.857335
           _cons |    10.14823    2.469212      4.11    0.000      5.308668      14.9878
-----------------+----------------------------------------------------------------
 Variance         |
       e.icdxcnt |     2.83528    .2174561                    2.439562     3.295188
         e.whpel |    791.7647    60.72558                    681.2585     920.1959
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.06, Prob > chi2 = 0.1508

. sem(avgcumdosew1->BSIdep)(BSIdep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIdep whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3112.3084
Iteration 1:   log likelihood = -3112.3084

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3112.3084

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIdep <-      |
    avgcumdosew1 |    .0407571    .0933205      0.44    0.662     -.1421478      .223662
           _cons |     8.11486     .160582     50.53    0.000      7.800125     8.429595
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIdep |    3.684326    .5298397      6.95    0.000       2.64586     4.722793
           _cons |   -6.771654    4.568981     -1.48    0.138     -15.72669     2.183384
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIdep |    8.221988    .6305977                    7.074449     9.555667
         e.whpel |    785.2146    60.22321                    675.6226     912.5834
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.50, Prob > chi2 = 0.1140

. sem(avgcumdosew1->BSIanx)(BSIanx->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIanx whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3093.2094
Iteration 1:   log likelihood = -3093.2094

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3093.2094

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIanx <-      |
    avgcumdosew1 |    .1520723    .0897252      1.69    0.090     -.0237858     .3279304
           _cons |    7.555319    .1543953     48.93    0.000      7.252709     7.857928
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIanx |    4.239198     .539721      7.85    0.000      3.181364     5.297031
           _cons |   -9.114591     4.37601     -2.08    0.037     -17.69141    -.5377688
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIanx |    7.600654    .5829436                    6.539835     8.833548
         e.whpel |    759.1408    58.22344                    653.1879     882.2802
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.12, Prob > chi2 = 0.2902

. sem(avgcumdosew1->PTSDw1)(PTSDw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  PTSDw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood =  -4014.537
Iteration 1:   log likelihood =  -4014.537

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -4014.537

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   PTSDw1 <-      |
    avgcumdosew1 |    2.025021    1.267074      1.60    0.110     -.4583978      4.50844
           _cons |    23.66027    2.180326     10.85    0.000      19.38691     27.93363
  ---------------+----------------------------------------------------------------
   whpel <-       |
          PTSDw1 |     .156492    .0406857      3.85    0.000      .0767495     .2362344
           _cons |    19.35193    1.877204     10.31    0.000      15.67268     23.03118
-----------------+----------------------------------------------------------------
 Variance         |
        e.PTSDw1 |    1515.745    116.2523                    1304.193     1761.612
         e.whpel |    859.4856    65.91954                    739.5277     998.9018
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.79, Prob > chi2 = 0.1805

. sem(avgcumdosew1->radfmw1)(radfmw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radfmw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3980.3951
Iteration 1:   log likelihood = -3980.3951

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3980.3951

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radfmw1 <-     |
    avgcumdosew1 |    1.273087    1.149507      1.11    0.268     -.9799062      3.52608
           _cons |    50.33594    1.978023     25.45    0.000      46.45909      54.2128
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radfmw1 |    .1844809    .0447976      4.12    0.000      .0966793     .2722826
           _cons |    13.80376    2.776376      4.97    0.000      8.362168     19.24536
-----------------+----------------------------------------------------------------
 Variance         |
       e.radfmw1 |    1247.515    95.68004                      1073.4     1449.873
         e.whpel |    854.2745    65.51986                    735.0439     992.8454
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.04, Prob > chi2 = 0.1534

. sem(avgcumdosew1->radtlw1)(radtlw1->whpel) if gender==1, nocapslatent
(1 observations with missing values excluded;
 specify option 'method(mlmv)' to use all observations)

Endogenous variables


Observed:  radtlw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3987.0762
Iteration 1:   log likelihood = -3987.0762

Structural equation model                       Number of obs      =       339
 Estimation method = ml
 Log likelihood    = -3987.0762

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radtlw1 <-     |
    avgcumdosew1 |   -.0299655    1.183144     -0.03    0.980     -2.348885     2.288954
           _cons |    53.53795    2.038815     26.26    0.000      49.54194     57.53395
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radtlw1 |    .0364577    .0447253      0.82    0.415     -.0512023     .1241176
           _cons |     21.3076     2.89387      7.36    0.000      15.63572     26.97948
-----------------+----------------------------------------------------------------
 Variance         |
       e.radtlw1 |    1321.568    101.5091                    1136.866     1536.279
         e.whpel |    896.1826    68.83537                    770.9321     1041.782
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.66, Prob > chi2 = 0.1028

. sem(avgcumdosew1->anxagw1)(anxagw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  anxagw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -4001.3496
Iteration 1:   log likelihood = -4001.3496

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4001.3496

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   anxagw1 <-     |
    avgcumdosew1 |    1.841356      1.2308      1.50    0.135     -.5709671     4.253679
           _cons |    23.38616    2.117908     11.04    0.000      19.23514     27.53718
  ---------------+----------------------------------------------------------------
   whpel <-       |
         anxagw1 |     .193641    .0414979      4.67    0.000      .1123066     .2749754
           _cons |    18.50903    1.866999      9.91    0.000      14.84978     22.16828
-----------------+----------------------------------------------------------------
 Variance         |
       e.anxagw1 |    1430.201    109.6914                    1230.589     1662.192
         e.whpel |    842.9036    64.64775                      725.26       979.63
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.71, Prob > chi2 = 0.1904

. sem(avgcumdosew1->HP2sxlife)(HP2sxlife->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  HP2sxlife whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -2445.3426
Iteration 1:   log likelihood = -2445.3426

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -2445.3426

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   HP2sxlife <-   |
    avgcumdosew1 |    .0155706    .0130621      1.19    0.233     -.0100307     .0411718
           _cons |    .1962583    .0224767      8.73    0.000      .1522047     .2403119
  ---------------+----------------------------------------------------------------
   whpel <-       |
       HP2sxlife |    25.39498    3.796194      6.69    0.000      17.95458     32.83539
           _cons |     18.0369    1.710147     10.55    0.000      14.68507     21.38873
-----------------+----------------------------------------------------------------
 Variance         |
     e.HP2sxlife |    .1610828    .0123545                    .1386006     .1872119
         e.whpel |    792.5673    60.78714                    681.9491     921.1287
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.71, Prob > chi2 = 0.1915

. sem(avgcumdosew1->drinkspww1)(drinkspww1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  drinkspww1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3086.6414
Iteration 1:   log likelihood = -3086.6414

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3086.6414

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   drinkspww1 <-  |
    avgcumdosew1 |    .0542741    .0815392      0.67    0.506     -.1055397     .2140879
           _cons |    1.367882    .1403091      9.75    0.000      1.092881     1.642883
  ---------------+----------------------------------------------------------------
   whpel <-       |
      drinkspww1 |     1.41043    .6433099      2.19    0.028      .1495659     2.671294
           _cons |    21.22843     1.84447     11.51    0.000      17.61334     24.84353
-----------------+----------------------------------------------------------------
 Variance         |
    e.drinkspww1 |    6.277037    .4814267                    5.400954     7.295228
         e.whpel |    884.3814    67.82895                    760.9487     1027.836
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      2.45, Prob > chi2 = 0.1174

. sem(avgcumdosew1->depagw1)(depagw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  depagw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood =  -3948.389
Iteration 1:   log likelihood =  -3948.389

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -3948.389

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   depagw1 <-     |
    avgcumdosew1 |    2.095672     1.04656      2.00    0.045      .0444527     4.146892
           _cons |    14.80642    1.800876      8.22    0.000      11.27677     18.33607
  ---------------+----------------------------------------------------------------
   whpel <-       |
         depagw1 |    .2030589    .0489895      4.14    0.000      .1070412     .2990766
           _cons |    20.00137     1.76154     11.35    0.000      16.54881     23.45393
-----------------+----------------------------------------------------------------
 Variance         |
       e.depagw1 |    1034.071    79.30964                    889.7465     1201.807
         e.whpel |     853.744    65.47918                    734.5874     992.2288
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.52, Prob > chi2 = 0.2182

. sem(avgcumdosew1->whpsleep)(whpsleep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  whpsleep whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3825.7475
Iteration 1:   log likelihood = -3825.7475

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3825.7475

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   whpsleep <-    |
    avgcumdosew1 |    1.902893    .8001588      2.38    0.017      .3346105     3.471175
           _cons |    16.48016    1.376879     11.97    0.000      13.78153     19.17879
  ---------------+----------------------------------------------------------------
   whpel <-       |
        whpsleep |     .551618    .0582892      9.46    0.000      .4373733     .6658628
           _cons |    13.64932    1.761942      7.75    0.000      10.19597     17.10266
-----------------+----------------------------------------------------------------
 Variance         |
      e.whpsleep |    604.4699    46.36072                    520.1043     702.5202
         e.whpel |    709.8956    54.44651                    610.8158     825.0469
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      0.39, Prob > chi2 = 0.5310

. sem(avgcumdosew1->fdferw1)(fdferw1->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  fdferw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -4006.1176
Iteration 1:   log likelihood = -4006.1176  (backed up)

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4006.1176

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   fdferw1 <-     |
    avgcumdosew1 |    1.806364    1.266485      1.43    0.154     -.6759022     4.288629
           _cons |    31.59529    2.179314     14.50    0.000      27.32392     35.86667
  ---------------+----------------------------------------------------------------
   whpel <-       |
         fdferw1 |    .2265222    .0397576      5.70    0.000      .1485987     .3044457
           _cons |    15.85793     2.01601      7.87    0.000      11.90662     19.80924
-----------------+----------------------------------------------------------------
 Variance         |
       e.fdferw1 |    1514.337    116.1444                    1302.982     1759.976
         e.whpel |    818.7156    62.79262                    704.4479     951.5185
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.62, Prob > chi2 = 0.2036

. sem(avgcumdosew1->goferw1)(goferw1-> whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  goferw1 whpel


Exogenous variables


Observed:  avgcumdosew1


Fitting target model:

Iteration 0:   log likelihood = -3959.7336
Iteration 1:   log likelihood = -3959.7336

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3959.7336

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   goferw1 <-     |
    avgcumdosew1 |    2.128628    1.076835      1.98    0.048      .0180712     4.239185
           _cons |    20.17463    1.852971     10.89    0.000      16.54287     23.80638
  ---------------+----------------------------------------------------------------
   whpel <-       |
         goferw1 |    .1773279    .0478508      3.71    0.000      .0835421     .2711136
           _cons |    19.45106    1.885137     10.32    0.000      15.75626     23.14586
-----------------+----------------------------------------------------------------
 Variance         |
       e.goferw1 |    1094.763    83.96452                    941.9678     1272.344
         e.whpel |     862.064    66.11729                    741.7462     1001.898
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      1.63, Prob > chi2 = 0.2020

.
. scalar W1MaleELMed = "radhlw1 and depagw1 "

. scalar W1numMELMeds = 2

. *-------------------------------------------------------------------------
. // r2 with basis functions = .323
. // r2 cha due to bf = .14
. ****************************** Wave 2 ******************************************
. // wave 2 model
.
. set more off

. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 childw2 ///
>   emplw22-emplw26 occ1w2-occ8w2 inc1w2-inc4w2 radhlw2 radchw2 ///
>   radtlw2 havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     dvcew2 sepaw2 ///
>    shhlw2 shhousw2 phlthw2 suprtw2 fdferw2 ///
>    dafter near chsize polprw2 icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     338
                                                       F( 48,   337) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4427
                                                       Root MSE      =  24.313

(Std. Err. adjusted for 338 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .3277932     .192719      1.70    0.090     -.0512904     .7068769
       educ2 |    20.05534    16.75697      1.20    0.232     -12.90609     53.01677
       educ3 |    22.56326     16.0254      1.41    0.160     -8.959161     54.08567
       educ4 |    20.27365    16.08671      1.26    0.208     -11.36938     51.91667
       educ5 |    30.62382    15.89774      1.93    0.055     -.6474797     61.89511
       educ6 |    24.56477    15.97333      1.54    0.125     -6.855228     55.98476
       educ7 |    22.98098    18.88947      1.22    0.225     -14.17513      60.1371
     marrw21 |    -8.68149    10.12862     -0.86    0.392     -28.60478      11.2418
     marrw22 |   -11.54657    11.36048     -1.02    0.310     -33.89295     10.79982
     marrw23 |   -13.75812    9.307615     -1.48    0.140     -32.06646     4.550224
     marrw25 |    -10.2331    13.80565     -0.74    0.459      -37.3892       16.923
     childw2 |   -.2772842    2.352155     -0.12    0.906     -4.904039     4.349471
     emplw22 |    10.66205    15.39281      0.69    0.489     -19.61604     40.94015
     emplw23 |    13.00872    15.33277      0.85    0.397     -17.15127     43.16872
     emplw24 |    24.46205    18.63584      1.31    0.190     -12.19519     61.11928
     emplw25 |      1.8521    18.52773      0.10    0.920     -34.59246     38.29666
     emplw26 |    3.733463    15.51268      0.24    0.810     -26.78042     34.24734
      occ1w2 |   -12.17144    13.54141     -0.90    0.369     -38.80778     14.46491
      occ2w2 |   -18.20682    13.17066     -1.38    0.168     -44.11388     7.700235
      occ3w2 |   -4.283118     14.4086     -0.30    0.766     -32.62524     24.05901
      occ4w2 |   -17.50013    13.72878     -1.27    0.203     -44.50503     9.504773
      occ5w2 |   -1.875849    14.10329     -0.13    0.894     -29.61742     25.86572
      occ6w2 |   -15.29873    14.47239     -1.06    0.291     -43.76634     13.16888
      occ7w2 |    -12.4741    16.50422     -0.76    0.450     -44.93837     19.99018
      occ8w2 |   -11.15978    13.71831     -0.81    0.417     -38.14408     15.82452
      inc1w2 |    16.26294    12.73885      1.28    0.203     -8.794732     41.32062
      inc2w2 |    7.269813    11.50885      0.63    0.528     -15.36843     29.90805
      inc3w2 |    13.81556    11.39457      1.21    0.226     -8.597881     36.22901
      inc4w2 |    3.251071    13.13962      0.25    0.805     -22.59494     29.09708
     radhlw2 |    .0384107    .0684703      0.56    0.575     -.0962723     .1730937
     radchw2 |    .1531813     .055549      2.76    0.006      .0439149     .2624477
     radtlw2 |    -.043716    .0560788     -0.78    0.436     -.1540245     .0665926
      havmil |    .0388161    .0280704      1.38    0.168     -.0163993     .0940314
      bfmEL2 |   -1.369128    .5845965     -2.34    0.020     -2.519046    -.2192104
      bfmEL4 |   -.3907642    .1276903     -3.06    0.002     -.6419346    -.1395937
     bfmEL16 |    .0354794    .0182082      1.95    0.052     -.0003367     .0712954
      carcin |   -.3744542    .1510166     -2.48    0.014     -.6715082    -.0774002
    healthef |    .2831364    .1691535      1.67    0.095     -.0495934     .6158662
      dvcew2 |   -.8904533    13.90712     -0.06    0.949     -28.24615     26.46524
      sepaw2 |   -10.03419    18.02081     -0.56    0.578     -45.48163     25.41325
      shhlw2 |    .0165975    .0563547      0.29    0.769     -.0942537     .1274487
    shhousw2 |    .0002076    .0518304      0.00    0.997     -.1017443     .1021594
     phlthw2 |   -.0070719    .1042823     -0.07    0.946     -.2121982     .1980544
     suprtw2 |    .0761874    .0379081      2.01    0.045      .0016211     .1507536
     fdferw2 |   -.0103074     .078675     -0.13    0.896     -.1650634     .1444486
      dafter |   -.0012409    .0111009     -0.11    0.911     -.0230766     .0205947
        near |   -.1457641    .0478445     -3.05    0.002     -.2398755    -.0516526
      chsize |   -.1319739    .0529356     -2.49    0.013     -.2360998     -.027848
     polprw2 |   -.0006481    .0526748     -0.01    0.990      -.104261     .1029648
     icdxcnt |    3.393045    1.080272      3.14    0.002      1.268119      5.51797
       _cons |    37782.05     11356.8      3.33    0.001       15442.9     60121.19
-------------+----------------------------------------------------------------

.
. scalar fw2wbfw2 = e(r2_a)

. set more off

.
.
. // Trimmed model with basis functions
. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 ///
>    radchw2 ///
>    havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     suprtw2  ///
>     near chsize  icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 22,   339) =   13.38
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3982
                                                       Root MSE      =  24.061

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .2702936    .1518737      1.78    0.076     -.0284398      .569027
       educ2 |    24.46738    14.38069      1.70    0.090     -3.819234       52.754
       educ3 |    22.01174    13.89683      1.58    0.114     -5.323137     49.34663
       educ4 |    17.96466    14.44739      1.24    0.215     -10.45315     46.38248
       educ5 |    30.09987    14.21458      2.12    0.035      2.139996     58.05975
       educ6 |     23.6291    14.05759      1.68    0.094     -4.021987     51.28019
       educ7 |    25.65155    17.19532      1.49    0.137     -8.171409     59.47451
     marrw21 |   -6.168838    7.434206     -0.83    0.407     -20.79182     8.454145
     marrw22 |   -9.106867     9.34958     -0.97    0.331     -27.49737     9.283631
     marrw23 |    -12.8066    6.937692     -1.85    0.066     -26.45295     .8397481
     marrw25 |   -14.27361    11.08311     -1.29    0.199     -36.07393     7.526718
     radchw2 |    .1220351    .0457406      2.67    0.008       .032064     .2120063
      havmil |     .029988    .0232715      1.29    0.198     -.0157866     .0757626
      bfmEL2 |    -1.58527    .5373359     -2.95    0.003     -2.642202     -.528337
      bfmEL4 |   -.4023972    .1161097     -3.47    0.001     -.6307833     -.174011
     bfmEL16 |    .0292467    .0158208      1.85    0.065     -.0018726     .0603659
      carcin |   -.5888307    .0862682     -6.83    0.000     -.7585191    -.4191422
    healthef |    .5014771    .1008121      4.97    0.000      .3031811      .699773
     suprtw2 |    .0750304     .035099      2.14    0.033       .005991     .1440697
        near |   -.1360927    .0433054     -3.14    0.002     -.2212738    -.0509115
      chsize |    -.132805    .0502016     -2.65    0.009      -.231551    -.0340591
     icdxcnt |    3.059986    .9817765      3.12    0.002      1.128845     4.991128
       _cons |     42921.3    9991.173      4.30    0.000       23268.8      62573.8
-------------+----------------------------------------------------------------

. scalar tw2wbfw2 = e(r2_a)

.
. // r2 without basis functions = .175
. set more off

. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 ///
>    radchw2 ///
>    havmil ///
>    carcin healthef ///
>     suprtw2  ///
>     near chsize  icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 19,   339) =    5.31
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1795
                                                       Root MSE      =  27.962

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .5860366    .1773065      3.31    0.001      .2372772      .934796
       educ2 |    23.70856      9.4506      2.51    0.013      5.119358     42.29776
       educ3 |    27.78232    7.767148      3.58    0.000      12.50444     43.06019
       educ4 |    23.49046    10.03198      2.34    0.020      3.757694     43.22323
       educ5 |    32.06349    9.105245      3.52    0.000      14.15359     49.97338
       educ6 |    26.47166     7.92116      3.34    0.001      10.89084     42.05247
       educ7 |    16.55252    12.77978      1.30    0.196     -8.585146     41.69018
     marrw21 |   -3.100339    9.914578     -0.31    0.755     -22.60218      16.4015
     marrw22 |   -7.309819    14.34793     -0.51    0.611       -35.532     20.91237
     marrw23 |   -8.044388    9.506162     -0.85    0.398     -26.74288      10.6541
     marrw25 |   -12.13521    14.02279     -0.87    0.387     -39.71786     15.44744
     radchw2 |    .0547825    .0494293      1.11    0.269     -.0424443     .1520093
      havmil |   -.0153093     .013498     -1.13    0.258     -.0418597     .0112412
      carcin |   -.6566249    .1352432     -4.86    0.000     -.9226466    -.3906033
    healthef |    .6803468    .1500252      4.53    0.000      .3852492     .9754443
     suprtw2 |    .0285286    .0406343      0.70    0.483     -.0513986     .1084558
        near |   -.0489141    .0498267     -0.98    0.327     -.1469225     .0490944
      chsize |   -.0837433    .0630771     -1.33    0.185     -.2078151     .0403286
     icdxcnt |    4.981234    1.130558      4.41    0.000      2.757441     7.205027
       _cons |   -32.40787    17.26055     -1.88    0.061     -66.35915     1.543403
-------------+----------------------------------------------------------------

.
. scalar tw2nobfw2 = e(r2_a)

. scalar w2numbfw2 = 3

. scalar list tw2nobfw2
 tw2nobfw2 =   .1308152

.
. scalar numModsw2 = 5

. scalar NumMedsw2= 2

.
. scalar r2chabfw2 = tw2wbfw2 - tw2nobfw2

. scalar avgImpBFw2 = r2chabfw2/w2numbfw2

. * avgImpBF = average improvement per basis function
. scalar list
W2maleELmed = age radfmw3 sleep, illww3 and Hp2sxlife
W2maleELMed = age and hp2sxlife
W1MaleELMed = radhlw1 and depagw1
w1maleELmods = age suprtw1 fdferw1 chsizew1 icdxcnt
w1numbmaleELmods =          5
w1numaleElmods =          5
 r2chabfw1 =  .07938894
     twbf2 =  .48490811
    twnobf =  .26459544
FemPainDoseMedsw3 = age illw3 phlthw3 radfmw3 hospw3 and radhlw3
    badout =          0
    ckcrit =  .31764707
  pctvalid =       62.5
pctinvalid =       37.5
 numMedFw2 =          1
FemPainW2Med = age
numbfsigfw2 =          9
   dsigfw2 =          0
       fw2 =  .57745936
FemPainW1Meds = educ and age
numModsigFw1 =          0
numbfsigfw1 =          1
numMainEffsigFw1 =          5
   dsigfw1 =          0
numMedPainDoseFsigw3 =          6
numbfsigTw3 =         15
numModsigTw3 =          0
numModsigFw3 =          0
numbfsigfw3 =         15
   dsigtw3 =          0
 numMedFw3 =         15
numMainEffsigTw3 =         16
   dsigfw3 =          0
numMainEffsigFw3 =         16
       fw3 =  .63678289
numbfsigtw2 =          0
 numMedMw2 =          2
   w2numbf =          7
numbfsigTw2 =          9
   tw2nobf =  .26459544
numModsigTw2 =          3
     tw2bf =  .29409811
numMainEffsigTw2 =          5
   dsigtw2 =          0
numbfsigMw2 =          0
numModsigFw2 =          2
numbfsigFw2 =          3
numMainEffsigFw2 =          8
   dsigFw2 =         .5
       mw2 =  .35574302
numModsigTw1 =          1
numMainEffsigTw1 =          5
numModsigMw1 =          0
   dsigtw1 =          3
numbfsigtw1 =          2
NumMainEffsigTw1 =         11
numbfsigMw1 =          1
numMainEffsigMw1 =          7
       Mw1 =  .28222811
   dsigMw1 =          1
        wv =          3
        pt =          1
       hyp =          1
W2FemaleELmed = age radfmw3 BSIanx BSIdep icdxcnt radhlw3 illw3 and Hp2sxlife
 numMedsw3 =          4
 numModsw3 =          1
  avgImpBF = -.01588267
 r2chabfw3 = -.04764801
   w3numbf =          3
   tw3bfw3 =  .39169032
W2FemaleELMed = age and radfmw2 radhlw2 radchw2 illw2 BSIanx BSIdep icdxcnt hp2sxlife
   tw3nobf =  .39169032
     tw3bf =  .34404231
    fw3wbf =  .33260096
 numMedsw2 =          2
   tw2bfw2 =  .48481206
avgImpBFw2 =  .07519191
 r2chabfw2 =  .22557574
 NumMedsw2 =          2
 numModsw2 =          5
 w2numbfw2 =          3
 tw2nobfw2 =   .1308152
  tw2wbfw2 =  .35639094
  fw2wbfw2 =  .34555619
W1numMELMeds =          2
W1FemaleELMed = age icdxcnt BSIdep depagw1 BSIanx anxagw1 PTSDw1 HP2sxlife
w1numMElMeds =          2
w1nuFemaleElmods =          0
avgImpBFw1 =  .05367898
   w1numbf =          3
   r2chabf =  .16103694
   tw1nobf =  .18797502
     tw1bf =  .34901196
       fw1 =  .37964479

. matrix define MaleWHPelr2w2 = (fw2, tw2bfw2, tw2nobfw2, w2numbfw2,  r2chabfw2, avgImpBFw2, numModsw2, NumMedsw2)

. matrix colnames MaleWHPelr2w2 = FullBFR2aw2 TR2aBFw2  TR2aNoBFw2  NumBFw2  BFR2chaw2  AvgImpBFw2 NumModsw2 NumMedsw2

. matrix rownames MaleWHPelr2w2 = wave2

. matlist MaleWHPelr2w2

   | FullBFR~2    TR2aBFw2    TR2aNoB~2    NumBFw2    BFR2chaw2    AvgImpB~2    NumModsw2    NumMedsw2
-------------+----------------------------------------------------------------------------------------
wave2   |  .5774594     .4848121     .1308152            3     .2255757     .0751919            5            2

.
. matrix define MaleWHPelr2 = (MaleWHPelr2w1 \ MaleWHPelr2w2)

. matlist MaleWHPelr2

   | FullBFR2a    TR2aBF    TR2aNoBF    NumBF    BFR2cha    AvgImpBF    w1numMods    w1numMeds
-------------+----------------------------------------------------------------------------------------
wave1   |  .3796448      .349012      .187975            3     .1610369      .053679            5            2
wave2   |  .5774594     .4848121     .1308152            3     .2255757     .0751919            5            2

.
.
. title "Wave 2 male  moderator analysis"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****                  Wave 2 male  moderator analysis                    *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:24  *****
*******************************************************************************
*******************************************************************************


.
.
. // Trimmed model with basis functions
. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 ///
>    radchw2 ///
>    havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     suprtw2  ///
>     near chsize  icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 22,   339) =   13.38
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3982
                                                       Root MSE      =  24.061

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .2702936    .1518737      1.78    0.076     -.0284398      .569027
       educ2 |    24.46738    14.38069      1.70    0.090     -3.819234       52.754
       educ3 |    22.01174    13.89683      1.58    0.114     -5.323137     49.34663
       educ4 |    17.96466    14.44739      1.24    0.215     -10.45315     46.38248
       educ5 |    30.09987    14.21458      2.12    0.035      2.139996     58.05975
       educ6 |     23.6291    14.05759      1.68    0.094     -4.021987     51.28019
       educ7 |    25.65155    17.19532      1.49    0.137     -8.171409     59.47451
     marrw21 |   -6.168838    7.434206     -0.83    0.407     -20.79182     8.454145
     marrw22 |   -9.106867     9.34958     -0.97    0.331     -27.49737     9.283631
     marrw23 |    -12.8066    6.937692     -1.85    0.066     -26.45295     .8397481
     marrw25 |   -14.27361    11.08311     -1.29    0.199     -36.07393     7.526718
     radchw2 |    .1220351    .0457406      2.67    0.008       .032064     .2120063
      havmil |     .029988    .0232715      1.29    0.198     -.0157866     .0757626
      bfmEL2 |    -1.58527    .5373359     -2.95    0.003     -2.642202     -.528337
      bfmEL4 |   -.4023972    .1161097     -3.47    0.001     -.6307833     -.174011
     bfmEL16 |    .0292467    .0158208      1.85    0.065     -.0018726     .0603659
      carcin |   -.5888307    .0862682     -6.83    0.000     -.7585191    -.4191422
    healthef |    .5014771    .1008121      4.97    0.000      .3031811      .699773
     suprtw2 |    .0750304     .035099      2.14    0.033       .005991     .1440697
        near |   -.1360927    .0433054     -3.14    0.002     -.2212738    -.0509115
      chsize |    -.132805    .0502016     -2.65    0.009      -.231551    -.0340591
     icdxcnt |    3.059986    .9817765      3.12    0.002      1.128845     4.991128
       _cons |     42921.3    9991.173      4.30    0.000       23268.8      62573.8
-------------+----------------------------------------------------------------

.
. foreach var in bfmEl2 bfmEL4 bfmEL6 carcin healthef near icdxcnt {
  2.   cap gen `var'Xd2 = `var'*avgcumdosew2
  3.   }

.
.
. // Trimmed model with basis functions
. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 ///
>    radchw2 ///
>    havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     suprtw2  ///
>     near chsize  icdxcnt bfmEL4Xd2-icdxcntXd2 if gender==1, vce(cluster id)
note: bfmEL6Xd2 omitted because of collinearity

Linear regression                                      Number of obs =     340
                                                       F( 26,   339) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4129
                                                       Root MSE      =  23.955

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .2421288    .1516368      1.60    0.111     -.0561388     .5403964
       educ2 |     23.6967    14.68099      1.61    0.107     -5.180611     52.57402
       educ3 |    21.25351    14.16992      1.50    0.135     -6.618537     49.12556
       educ4 |     17.3952    14.71755      1.18    0.238     -11.55401     46.34441
       educ5 |    28.10652    14.56568      1.93    0.054     -.5439717     56.75701
       educ6 |    22.45317    14.29669      1.57    0.117     -5.668225     50.57456
       educ7 |    24.93462    17.53378      1.42    0.156     -9.554093     59.42332
     marrw21 |   -6.493675    7.478988     -0.87    0.386     -21.20474     8.217392
     marrw22 |   -9.251759    9.438242     -0.98    0.328     -27.81665     9.313135
     marrw23 |   -13.68417    6.989104     -1.96    0.051     -27.43164      .063304
     marrw25 |   -16.70559    11.87233     -1.41    0.160     -40.05829     6.647112
     radchw2 |      .11655    .0460394      2.53    0.012      .0259912     .2071089
      havmil |    .0280993    .0231175      1.22    0.225     -.0173726     .0735712
      bfmEL2 |   -1.666796    .5332022     -3.13    0.002     -2.715598    -.6179949
      bfmEL4 |   -.3857775    .1168462     -3.30    0.001     -.6156124    -.1559425
     bfmEL16 |    .0269654    .0157633      1.71    0.088     -.0040408     .0579715
      carcin |   -.4676663    .2309403     -2.03    0.044     -.9219228    -.0134099
    healthef |    .4098274    .2421788      1.69    0.092     -.0665349     .8861897
     suprtw2 |     .069914     .035319      1.98    0.049       .000442      .139386
        near |   -.0907609    .0631736     -1.44    0.152     -.2150225     .0335007
      chsize |   -.1505494    .0505367     -2.98    0.003     -.2499544    -.0511444
     icdxcnt |    3.692648    1.335344      2.77    0.006      1.066044     6.319252
   bfmEL4Xd2 |    .0004242    .0003856      1.10    0.272     -.0003343     .0011827
   bfmEL6Xd2 |           0   (omitted)
   carcinXd2 |   -.4374171    1.030643     -0.42    0.672     -2.464678     1.589844
 healthefXd2 |    .4084727    1.036982      0.39    0.694     -1.631257     2.448203
     nearXd2 |   -.0578182    .0672782     -0.86    0.391     -.1901534     .0745171
  icdxcntXd2 |   -.7819446    1.149152     -0.68    0.497      -3.04231     1.478421
       _cons |    44391.29    9905.229      4.48    0.000      24907.83     63874.74
-------------+----------------------------------------------------------------

. // no moderator effects are significant at wave 2
.
.
. title "Wave 2 male mediation analysis"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****                   Wave 2 male mediation analysis                    *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:24  *****
*******************************************************************************
*******************************************************************************


.
. title "age and sex life are possible male mediators of energy level in wave 2"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****age and sex life are possible male mediators of energy level in wave 2*****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:24  *****
*******************************************************************************
*******************************************************************************


.
. cap gen whpel = WHPel

. sem(avgcumdosew2->age)(age->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  age whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood =  -3750.439
Iteration 1:   log likelihood =  -3750.439

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -3750.439

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   age <-         |
    avgcumdosew2 |    .5832314    .2628107      2.22    0.026      .0681318     1.098331
           _cons |    48.62133    .7040762     69.06    0.000      47.24136     50.00129
  ---------------+----------------------------------------------------------------
   whpel <-       |
             age |    .6520247    .1282979      5.08    0.000      .4005655     .9034839
           _cons |   -8.877521    6.501358     -1.37    0.172     -21.61995     3.864907
-----------------+----------------------------------------------------------------
 Variance         |
           e.age |    146.8166    11.26032                    126.3255     170.6315
         e.whpel |    833.5635     63.9314                    717.2235     968.7748
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.11, Prob > chi2 = 0.0238

. sem(avgcumdosew2->illw2)(illw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  illw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -2732.9741
Iteration 1:   log likelihood = -2732.9741

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -2732.9741

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   illw2 <-       |
    avgcumdosew2 |    .0085423    .0128178      0.67    0.505     -.0165801     .0336647
           _cons |    .2741359    .0343391      7.98    0.000      .2068324     .3414394
  ---------------+----------------------------------------------------------------
   whpel <-       |
           illw2 |    6.594973    2.723166      2.42    0.015      1.257665     11.93228
           _cons |    21.32848    1.784478     11.95    0.000      17.83097     24.82599
-----------------+----------------------------------------------------------------
 Variance         |
         e.illw2 |    .3492324    .0267849                    .3004902      .405881
         e.whpel |    881.6754    67.62142                    758.6204     1024.691
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.25, Prob > chi2 = 0.0071

. sem(avgcumdosew2->radchw2)(radchw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radchw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -4111.8667
Iteration 1:   log likelihood = -4111.8667

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4111.8667

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radchw2 <-     |
    avgcumdosew2 |    1.121598    .7344428      1.53    0.127     -.3178833      2.56108
           _cons |    47.60346     1.96759     24.19    0.000      43.74706     51.45987
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radchw2 |    .0442927    .0477412      0.93    0.354     -.0492783     .1378636
           _cons |    21.03432     2.83424      7.42    0.000      15.47931     26.58933
-----------------+----------------------------------------------------------------
 Variance         |
       e.radchw2 |    1146.581    87.93878                    986.5537     1332.567
         e.whpel |    894.6198    68.61421                    769.7582     1039.735
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.24, Prob > chi2 = 0.0071

. sem(avgcumdosew2->radhlw2)(radhlw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radhlw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -4109.1774
Iteration 1:   log likelihood = -4109.1774

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4109.1774

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radhlw2 <-     |
    avgcumdosew2 |    1.220373    .7639591      1.60    0.110     -.2769597     2.717705
           _cons |    45.63198    2.046665     22.30    0.000      41.62059     49.64337
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radhlw2 |    .2577464    .0437617      5.89    0.000      .1719751     .3435178
           _cons |    11.12654     2.56695      4.33    0.000       6.09541     16.15767
-----------------+----------------------------------------------------------------
 Variance         |
       e.radhlw2 |    1240.593     95.1491                    1067.444     1441.828
         e.whpel |    813.8495    62.41941                     700.261     945.8631
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.70, Prob > chi2 = 0.0169

. sem(avgcumdosew2->icdxcnt)(icdxcnt->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  icdxcnt whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3070.1668
Iteration 1:   log likelihood = -3070.1668

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3070.1668

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   icdxcnt <-     |
    avgcumdosew2 |    .0482004    .0364651      1.32    0.186       -.02327     .1196707
           _cons |    2.097753    .0976909     21.47    0.000      1.906282     2.289223
  ---------------+----------------------------------------------------------------
   whpel <-       |
         icdxcnt |    6.082854    .9053643      6.72    0.000      4.308372     7.857335
           _cons |    10.14823    2.469212      4.11    0.000      5.308668      14.9878
-----------------+----------------------------------------------------------------
 Variance         |
       e.icdxcnt |     2.82647    .2167804                    2.431981     3.284948
         e.whpel |    791.7647    60.72558                    681.2585     920.1959
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.02, Prob > chi2 = 0.0141

. sem(avgcumdosew2->BSIdep)(BSIdep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIdep whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3249.9872
Iteration 1:   log likelihood = -3249.9872

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3249.9872

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIdep <-      |
    avgcumdosew2 |    .0546271    .0621402      0.88    0.379     -.0671655     .1764197
           _cons |    8.079806    .1664751     48.53    0.000      7.753521     8.406091
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIdep |    3.684326    .5298397      6.95    0.000       2.64586     4.722793
           _cons |   -6.771654    4.568981     -1.48    0.138     -15.72669     2.183384
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIdep |    8.207944    .6295206                    7.062366     9.539345
         e.whpel |    785.2146    60.22321                    675.6226     912.5834
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.84, Prob > chi2 = 0.0089

. sem(avgcumdosew2->BSIanx)(BSIanx->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIanx whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3231.5028
Iteration 1:   log likelihood = -3231.5028

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3231.5028

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIanx <-      |
    avgcumdosew2 |    .0891716    .0598542      1.49    0.136     -.0281406     .2064838
           _cons |    7.534812     .160351     46.99    0.000       7.22053     7.849094
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIanx |    4.239198     .539721      7.85    0.000      3.181364     5.297031
           _cons |   -9.114591     4.37601     -2.08    0.037     -17.69141    -.5377688
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIanx |    7.615158     .584056                    6.552315     8.850404
         e.whpel |    759.1408    58.22344                    653.1879     882.2802
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.59, Prob > chi2 = 0.0181

. sem(avgcumdosew2->PTSDw2)(PTSDw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  PTSDw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3774.6382
Iteration 1:   log likelihood = -3774.6382

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3774.6382

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   PTSDw2 <-      |
    avgcumdosew2 |   -.0429879    .2746329     -0.16    0.876     -.5812585     .4952828
           _cons |    5.196645    .7357482      7.06    0.000      3.754605     6.638685
  ---------------+----------------------------------------------------------------
   whpel <-       |
          PTSDw2 |    .3233827    .1270627      2.55    0.011      .0743444     .5724211
           _cons |    21.52346    1.737143     12.39    0.000      18.11872     24.92819
-----------------+----------------------------------------------------------------
 Variance         |
        e.PTSDw2 |    160.3224    12.29617                    137.9463     186.3281
         e.whpel |    880.1175    67.50193                      757.28      1022.88
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.87, Prob > chi2 = 0.0050

. sem(avgcumdosew2->radfmw2)(radfmw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radfmw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -4100.4947
Iteration 1:   log likelihood = -4100.4947

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4100.4947

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radfmw2 <-     |
    avgcumdosew2 |    .8365725    .7409603      1.13    0.259      -.615683     2.288828
           _cons |    55.20999     1.98505     27.81    0.000      51.31936     59.10061
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radfmw2 |     .252708    .0454323      5.56    0.000      .1636623     .3417537
           _cons |    9.035226    2.982328      3.03    0.002       3.18997     14.88048
-----------------+----------------------------------------------------------------
 Variance         |
       e.radfmw2 |    1167.021    89.50646                    1004.141     1356.323
         e.whpel |    822.0777    63.05048                    707.3408      955.426
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.45, Prob > chi2 = 0.0111

. sem(avgcumdosew2->radtlw2)(radtlw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radtlw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -4121.0144
Iteration 1:   log likelihood = -4121.0144

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4121.0144

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radtlw2 <-     |
    avgcumdosew2 |    .3299338    .7547777      0.44    0.662     -1.149403     1.809271
           _cons |    51.63557    2.022068     25.54    0.000      47.67239     55.59875
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radtlw2 |    .0496846     .046582      1.07    0.286     -.0416144     .1409836
           _cons |    20.60933    2.913047      7.07    0.000      14.89986     26.31879
-----------------+----------------------------------------------------------------
 Variance         |
       e.radtlw2 |    1210.953    92.87582                    1041.941      1407.38
         e.whpel |    893.8936    68.55851                    769.1334     1038.891
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.49, Prob > chi2 = 0.0062

. sem(avgcumdosew2->anxagw2)(anxagw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  anxagw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3901.1257
Iteration 1:   log likelihood = -3901.1257

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3901.1257

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   anxagw2 <-     |
    avgcumdosew2 |    .1453454      .40215      0.36    0.718     -.6428541     .9335449
           _cons |    9.079306    1.077369      8.43    0.000      6.967701     11.19091
  ---------------+----------------------------------------------------------------
   whpel <-       |
         anxagw2 |    .3102537    .0859501      3.61    0.000      .1417945     .4787129
           _cons |    20.33032    1.780002     11.42    0.000      16.84158     23.81906
-----------------+----------------------------------------------------------------
 Variance         |
       e.anxagw2 |    343.7677    26.36578                    295.7882     399.5299
         e.whpel |    863.7817    66.24904                    743.2242     1003.895
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.50, Prob > chi2 = 0.0062

. sem(avgcumdosew2->HP2sxlife)(HP2sxlife->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  HP2sxlife whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -2581.7136
Iteration 1:   log likelihood = -2581.7136

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -2581.7136

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   HP2sxlife <-   |
    avgcumdosew2 |    .0186763    .0086644      2.16    0.031      .0016944     .0356582
           _cons |     .184976    .0232121      7.97    0.000      .1394811      .230471
  ---------------+----------------------------------------------------------------
   whpel <-       |
       HP2sxlife |    25.39498    3.796194      6.69    0.000      17.95458     32.83539
           _cons |     18.0369    1.710147     10.55    0.000      14.68507     21.38873
-----------------+----------------------------------------------------------------
 Variance         |
     e.HP2sxlife |    .1595754    .0122389                    .1373035     .1854599
         e.whpel |    792.5673    60.78714                    681.9491     921.1287
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      4.67, Prob > chi2 = 0.0307

. sem(avgcumdosew2->drinkspww2)(drinkspww2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  drinkspww2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3181.4492
Iteration 1:   log likelihood = -3181.4492

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3181.4492

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   drinkspww2 <-  |
    avgcumdosew2 |    .0455163    .0476342      0.96    0.339     -.0478451     .1388777
           _cons |    1.530923    .1276133     12.00    0.000      1.280805      1.78104
  ---------------+----------------------------------------------------------------
   whpel <-       |
      drinkspww2 |    .9076404    .7369126      1.23    0.218     -.5366818     2.351963
           _cons |    21.76132    1.993177     10.92    0.000      17.85477     25.66788
-----------------+----------------------------------------------------------------
 Variance         |
    e.drinkspww2 |    4.823114    .3699159                    4.149954     5.605466
         e.whpel |    892.9006    68.48235                     768.279     1037.737
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.30, Prob > chi2 = 0.0069

. sem(avgcumdosew2->depagw2)(depagw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  depagw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3867.5441
Iteration 1:   log likelihood = -3867.5441

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3867.5441

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   depagw2 <-     |
    avgcumdosew2 |    .5814392    .3640538      1.60    0.110     -.1320932     1.294972
           _cons |    7.931876    .9753089      8.13    0.000      6.020306     9.843447
  ---------------+----------------------------------------------------------------
   whpel <-       |
         depagw2 |    .3347175    .0946797      3.54    0.000      .1491488     .5202863
           _cons |    20.34844     1.78625     11.39    0.000      16.84746     23.84943
-----------------+----------------------------------------------------------------
 Variance         |
       e.depagw2 |    281.7216    21.60706                    242.4019     327.4194
         e.whpel |    865.0849    66.34898                    744.3455     1005.409
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.29, Prob > chi2 = 0.0122

. sem(avgcumdosew2->whpsleep)(whpsleep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  whpsleep whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3964.6753
Iteration 1:   log likelihood = -3964.6753

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3964.6753

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   whpsleep <-    |
    avgcumdosew2 |    1.030356    .5347701      1.93    0.054     -.0177741     2.078486
           _cons |    16.30576    1.432662     11.38    0.000      13.49779     19.11372
  ---------------+----------------------------------------------------------------
   whpel <-       |
        whpsleep |     .551618    .0582892      9.46    0.000      .4373733     .6658628
           _cons |    13.64932    1.761942      7.75    0.000      10.19597     17.10266
-----------------+----------------------------------------------------------------
 Variance         |
      e.whpsleep |    607.8874    46.62284                    523.0449     706.4921
         e.whpel |    709.8956    54.44651                    610.8158     825.0469
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      4.48, Prob > chi2 = 0.0343

. sem(avgcumdosew2->fdferw2)(fdferw2->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  fdferw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -4038.5918
Iteration 1:   log likelihood = -4038.5918

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4038.5918

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   fdferw2 <-     |
    avgcumdosew2 |    .2865327    .6101081      0.47    0.639     -.9092572     1.482323
           _cons |     16.0332    1.634494      9.81    0.000      12.82965     19.23675
  ---------------+----------------------------------------------------------------
   whpel <-       |
         fdferw2 |    .2621922    .0559425      4.69    0.000      .1525468     .3718376
           _cons |    18.91454    1.819398     10.40    0.000      15.34859      22.4805
-----------------+----------------------------------------------------------------
 Variance         |
       e.fdferw2 |    791.2296    60.68454                    680.7981      919.574
         e.whpel |    842.4565    64.61346                    724.8753     979.1104
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.42, Prob > chi2 = 0.0064

. sem(avgcumdosew2->goferw2)(goferw2-> whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  goferw2 whpel


Exogenous variables


Observed:  avgcumdosew2


Fitting target model:

Iteration 0:   log likelihood = -3866.9219
Iteration 1:   log likelihood = -3866.9219

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3866.9219

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   goferw2 <-     |
    avgcumdosew2 |    .5291007    .3615845      1.46    0.143     -.1795918     1.237793
           _cons |    6.791045    .9686934      7.01    0.000      4.892441      8.68965
  ---------------+----------------------------------------------------------------
   whpel <-       |
         goferw2 |    .2876925    .0958592      3.00    0.003       .099812      .475573
           _cons |    21.09043    1.749142     12.06    0.000      17.66218     24.51869
-----------------+----------------------------------------------------------------
 Variance         |
       e.goferw2 |    277.9127    21.31493                    239.1246     322.9927
         e.whpel |    873.7378    67.01263                    751.7907     1015.466
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.55, Prob > chi2 = 0.0105

.
.
. scalar W2maleELMed = "age and hp2sxlife"

. scalar numMedsw2= 2

. scalar numModsw2 = 0

. *****************************  Wave 3 ******************************************
. *-------------------------------------------------------------------------------
.
. title "Wave three male dose- energy level response model"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****         Wave three male dose- energy level response model           *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:27  *****
*******************************************************************************
*******************************************************************************


.
. set more off

. des WHPel age educ2-educ7 marrw31-marrw33 marrw35 childw3 ///
>   emplw32-emplw35 occ1w3-occ8w3 inc1w3-inc4w3 radhlw3 radchw3 ///
>   radtlw3 havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef dvcew3 sepaw3 shhlw3 shhousw3 phlthw3 suprtw3 fdferw3 ///
>    dafter near chsize polprw3 icdxcnt

              storage  display     value
variable name   type   format      label      variable label
-------------


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


age               byte     %8.0g                    *   Respondent's age


educ2             byte     %8.0g                        educ==2. graduated high school


educ3             byte     %8.0g                        educ==3. technical degree


educ4             byte     %8.0g                        educ==4. did not finish college/bachelor's


educ5             byte     %8.0g                        educ==5. graduated college/bachelor's


educ6             byte     %8.0g                        educ==6. finished specialist/master's degree


educ7             byte     %8.0g                        educ==7. doctor of science/phd


marrw31           byte     %8.0g                        marrw3==1. single


marrw32           byte     %8.0g                        marrw3==2. cohabitating


marrw33           byte     %8.0g                        marrw3==3. married


marrw35           byte     %8.0g                        marrw3==5. divorced


childw3           byte     %8.0g                        number of children now


emplw32           byte     %8.0g                        emplw3==2. part time


emplw33           byte     %8.0g                        emplw3==4. retired


emplw34           byte     %8.0g                        emplw3==5. unemployed


emplw3            byte     %15.0g        LABI           mode of employment now


occ1w1            byte     %15.0g        LABJ           profess executive administration in 1986


occ2w1            byte     %15.0g        LABJ           technical sales admin support  in 1986


occ3w1            byte     %15.0g        LABJ           service occup protective services  in 1986


occ4w1            byte     %15.0g        LABJ           precision prod mechan craft construction  in 1986


occ5w1            byte     %15.0g        LABJ           factory laborer machinist transp cleaner  in 1986


occ6w1            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging  in 1986


occ7w1            byte     %15.0g        LABJ           homemaking or caregiving  in 1986


occ8w1            byte     %15.0g        LABJ           student  in 1986


occ1w2            byte     %15.0g        LABJ           profess executive administration in 1996


occ2w2            byte     %15.0g        LABJ           technical sales admin support in 1996


occ3w2            byte     %15.0g        LABJ           service occup protective services in 1996


occ4w2            byte     %15.0g        LABJ           precision prod mechan craft construction in 1996


occ5w2            byte     %15.0g        LABJ           factory laborer machinist transp cleaner in 1996


occ6w2            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging in 1996


occ7w2            byte     %15.0g        LABJ           homemaking caregiving in 1996


occ8w2            byte     %15.0g        LABJ           student in 1996


occ1w3            byte     %15.0g        LABJ           professional executive administration now


occ2w3            byte     %15.0g        LABJ           technical sales admin support now


occ3w3            byte     %15.0g        LABJ           service occup protective services now


occ4w3            byte     %15.0g        LABJ           precision prod mechan craft construction now


occ5w3            byte     %15.0g        LABJ           factory laborer machinist transp cleaner now


occ6w3            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging now


occ7w3            byte     %15.0g        LABJ           homemaking or caregiving now


occ8w3            byte     %15.0g        LABJ           student now


inc1w1            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities in 1986


inc2w1            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities in 1986


inc3w1            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings in 1986


inc4w1            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items in 1986


inc1w2            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities in 1996


inc2w2            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities in 1996


inc3w2            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings in 1996


inc4w2            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items in 1996


inc1w3            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities NOW


inc2w3            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities NOW


inc3w3            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings NOW


inc4w3            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items NOW


jsw1              byte     %8.0g                        Job satisfaction on a scale of 0-100% in 1986


jsw2              byte     %8.0g                        Job satisfaction on a scale of 0-100% in 1996


jsw3              byte     %8.0g                        Job satisfaction on a scale of 0-100%  NOW


deaw1             byte     %8.0g                        Total number of death experienced in time period 1986


deaw2             byte     %8.0g                        Total number of death experienced in time period 1996


deaw3             byte     %8.0g                        Total number of death experienced in time period 1996-NOW


dvcew1            byte     %8.0g                        Total number of divorces experienced in time period 1976-1986


dvcew2            byte     %8.0g                        Total number of divorces experienced in time period 1987-1996


dvcew3            byte     %8.0g                        Total number of divorces experienced in time period 1996-NOW


sepaw1            byte     %8.0g                        Total number of separations experienced in time period 1976-1986


sepaw2            byte     %8.0g                        Total number of separations experienced in time period 1987-1996


sepaw3            byte     %8.0g                        Total number of separations experienced in time period 1996-NOW


accdw1            byte     %8.0g                        Total number of accidents experienced in time period 1976-1986


accdw2            byte     %8.0g                        Total number of accidents experienced in time period 1987-1996


accdw3            byte     %8.0g                        Total number of accidents experienced in time period 1996-NOW


cataw1            byte     %8.0g                        Total number of disasters experienced in time period 1976-1986


cataw2            byte     %8.0g                        Total number of disasters experienced in time period 1987-1996


cataw3            byte     %8.0g                        Total number of disasters experienced in time period 1996-NOW


illw1             byte     %8.0g                        Total number of illnesses experienced in time period 1976-1986


illw2             byte     %8.0g                        Total number of illnesses experienced in time period 1987-1996


illw3             byte     %8.0g                        Total number of illnesses experienced in time period 1996-NOW


movew1            byte     %8.0g                        Total number of moves experienced in time period 1976-1986


movew2            byte     %8.0g                        Total number of moves experienced in time period 1987-1996


movew3            byte     %8.0g                        Total number of moves experienced in time period 1996-NOW


shjobw1           byte     %8.0g                        Percentage of strains and hassles related to job in 1986


shjobw2           byte     %8.0g                        Percentage of strains and hassles related to job in 1996


shjobw3           byte     %8.0g                    *   Percentage of strains and hassles related to job NOW


shfamw1           byte     %8.0g                        Percentage of strains and hassles related to family in 1986


shfamw2           byte     %8.0g                        Percentage of strains and hassles related to family in 1996


shfamw3           byte     %8.0g                        Percentage of strains and hassles related to family NOW


shhlw1            byte     %8.0g                        Percentage of strains and hassles related to health in 1986


shhlw2            byte     %8.0g                        Percentage of strains and hassles related to health in 1996


shhlw3            byte     %8.0g                        Percentage of strains and hassles related to health NOW


shfincw1          byte     %8.0g                        Percentage of strains and hassles related to finances in 1986


shfincw2          byte     %8.0g                        Percentage of strains and hassles related to finances in 1996


shfincw3          byte     %8.0g                        Percentage of strains and hassles related to finances NOW


shhousw1          byte     %8.0g                        Percentage of strains and hassles related to housing in 1986


shhousw2          byte     %8.0g                        Percentage of strains and hassles related to housing in 1996


shhousw3          byte     %8.0g                        Percentage of strains and hassles related to housing NOW


shrelaw1          byte     %8.0g                        Percentage of strains and hassles related to relationships in 1986


shrelaw2          byte     %8.0g                        Percentage of strains and hassles related to relationships in 1996


shrelaw3          byte     %8.0g                        Percentage of strains and hassles related to relationships NOW


suprtw1           byte     %8.0g                        Level of support (in percent) from partner in 1986


suprtw2           byte     %8.0g                        Level of support (in percent) from partner in 1996


suprtw3           byte     %8.0g                        Level of support (in percent) from partner NOW


sufamw1           byte     %8.0g                        Level of support (in percent) from family in 1986


sufamw2           byte     %8.0g                        Level of support (in percent) from family in 1996


sufamw3           byte     %8.0g                        Level of support (in percent) from family in NOW


suchrw1           byte     %8.0g                        Level of support (in percent) from Chernobyl survivor benefits in 1986


suchrw2           byte     %8.0g                        Level of support (in percent) from Chernobyl survivor benefits in 1996


suchrw3           byte     %8.0g                        Level of support (in percent) from Chernobyl survivor benefits NOW


phlthw1           byte     %8.0g                        level of general physical health in 1986


phlthw2           byte     %8.0g                        level of general physical health in 1996


phlthw3           byte     %8.0g                        level of general physical health now


mhlthw1           byte     %8.0g                        level of general psychological/mental health in 1986


mhlthw2           byte     %8.0g                        level of general psychological/mental health in 1996


mhlthw3           byte     %8.0g                        level of general psychological/mental health now


nil1w1            byte     %26.0g        ill862         name of illness 1 in time period from 1977 to 1986


nil2w1            byte     %26.0g        ill862         name of illness 2 in time period from 1977 to 1986


nil3w1            byte     %26.0g        ill862         name of illness 3 in time period from 1977 to 1986


nil4w1            byte     %26.0g        ill862         name of illness 4 in time period from 1977 to 1986


nil5w1            byte     %26.0g        ill862         name of illness 5 in time period from 1977 to 1986


nil6w1            byte     %26.0g        ill862         name of illness 6 in time period from 1977 to 1986


nil7w1            byte     %26.0g        ill862         name of illness 7 in time period from 1977 to 1986


nil8w1            byte     %26.0g        ill862         name of illness 8 in time period from 1977 to 1986


nil9w1            byte     %26.0g        ill862         name of illness 9 in time period from 1977 to 1986


nil10w1           byte     %26.0g        ill862         name of illness 10 in time period from 1977 to 1986


dil1w1            long     %d                           date of onset for illness 1 in time period from 1977 to 1986


dil2w1            int      %d                           date of onset for illness 2 in time period from 1977 to 1986


dil3w1            int      %d                           date of onset for illness 3 in time period from 1977 to 1986


dil4w1            int      %d                           date of onset for illness 4 in time period from 1977 to 1986


dil5w1            int      %d                           date of onset for illness 5 in time period from 1977 to 1986


dil6w1            byte     %d                           date of onset for illness 6 in time period from 1977 to 1986


dil7w1            byte     %d                           date of onset for illness 7 in time period from 1977 to 1986


dil8w1            byte     %d                           date of onset for illness 8 in time period from 1977 to 1986


dil9w1            byte     %d                           date of onset for illness 9 in time period from 1977 to 1986


dil10w1           byte     %d                           date of onset for illness 10 in time period from 1977 to 1986


dril1w1           double   %9.0g                        duration of illness 1 in years in time period from 1977 to 1986


dril2w1           double   %9.0g                        duration of illness 2 in years in time period from 1977 to 1986


dril3w1           byte     %8.0g                        duration of illness 3 in years in time period from 1977 to 1986


dril4w1           byte     %8.0g                        duration of illness 4 in years in time period from 1977 to 1986


dril5w1           byte     %8.0g                        duration of illness 5 in years in time period from 1977 to 1986


dril6w1           byte     %8.0g                        duration of illness 6 in years in time period from 1977 to 1986


dril7w1           byte     %8.0g                        duration of illness 7 in years in time period from 1977 to 1986


dril8w1           byte     %8.0g                        duration of illness 8 in years in time period from 1977 to 1986


dril9w1           byte     %8.0g                        duration of illness 9 in years in time period from 1977 to 1986


dril10w1          byte     %8.0g                        duration of illness 10 in years in time period from 1977 to 1986


pil1w1            byte     %15.0g        LABC           persistence of illness 1 in time period fro 1977 to 1986


pil2w1            byte     %15.0g        LABC           persistence of illness 2 in time period fro 1977 to 1986


pil3w1            byte     %15.0g        LABC           persistence of illness 3 in time period fro 1977 to 1986


pil4w1            byte     %15.0g        LABC           persistence of illness 4 in time period fro 1977 to 1986


pil5w1            byte     %15.0g        LABC           persistence of illness 5 in time period fro 1977 to 1986


pil6w1            byte     %15.0g        LABC           persistence of illness 6 in time period fro 1977 to 1986


pil7w1            byte     %15.0g        LABC           persistence of illness 7 in time period fro 1977 to 1986


pil8w1            byte     %15.0g        LABC           persistence of illness 8 in time period fro 1977 to 1986


pil9w1            byte     %15.0g        LABC           persistence of illness 9 in time period fro 1977 to 1986


pil10w1           byte     %15.0g        LABC           persistence of illness 10 in time period fro 1977 to 1986


nil1w2            byte     %26.0g        ill862         name of illness 1 in time period from 1987-1996


nil2w2            byte     %26.0g        ill862         name of illness 2 in time period from 1987-1996


nil3w2            byte     %26.0g        ill862         name of illness 3 in time period from 1987-1996


nil4w2            byte     %26.0g        ill862         name of illness 4 in time period from 1987-1996


nil5w2            byte     %26.0g        ill862         name of illness 5 in time period from 1987-1996


nil6w2            byte     %26.0g        ill862         name of illness 6 in time period from 1987-1996


nil7w2            byte     %26.0g        ill862         name of illness 7 in time period from 1987-1996


nil8w2            byte     %26.0g        ill862         name of illness 8 in time period from 1987-1996


nil9w2            byte     %26.0g        ill862         name of illness 9 in time period from 1987-1996


nil10w2           byte     %26.0g        ill862         name of illness 10 in time period from 1987-1996


dil1w2            long     %d                           date of onset of illness 1 in time period from 1987-1996


dil2w2            long     %d                           date of onset of illness 2 in time period from 1987-1996


dil3w2            int      %d                           date of onset of illness 3 in time period from 1987-1996


dil4w2            int      %d                           date of onset of illness 4 in time period from 1987-1996


dil5w2            int      %d                           date of onset of illness 5 in time period from 1987-1996


dil6w2            int      %d                           date of onset of illness 6 in time period from 1987-1996


dil7w2            int      %d                           date of onset of illness 7  in time period from 1987-1996


dil8w2            byte     %d                           date of onset of illness 8 in time period from 1987-1996


dil9w2            byte     %d                           date of onset of illness 9 in time period from 1987-1996


dil10w2           byte     %d                           date of onset of illness 10 in time period from 1987-1996


dril1w2           double   %9.0g                        duration of illness 1 in years in time period from 1987 to 1996


dril2w2           byte     %9.0g                        duration of illness 2 in years in time period from 1987 to 1996


dril3w2           byte     %8.0g                        duration of illness 3 in years in time period from 1987 to 1996


dril4w2           byte     %8.0g                        duration of illness 4 in years in time period from 1987 to 1996


dril5w2           byte     %8.0g                        duration of illness 5 in years in time period from 1987 to 1996


dril6w2           byte     %8.0g                        duration of illness 6 in years in time period from 1987 to 1996


dril7w2           byte     %8.0g                        duration of illness 7 in years in time period from 1987 to 1996


dril8w2           byte     %8.0g                        duration of illness 8 in years in time period from 1987 to 1996


dril9w2           byte     %8.0g                        duration of illness 9 in years in time period from 1987 to 1996


dril10w2          byte     %8.0g                        duration of illness 10 in years in time period from 1987 to 1996


pil1w2            byte     %15.0g        LABC           persistence of illness 1 in time period from 1987 to 1996


pil2w2            byte     %15.0g        LABC           persistence of illness 2 in time period from 1987 to 1996


pil3w2            byte     %15.0g        LABC           persistence of illness 3 in time period from 1987 to 1996


pil4w2            byte     %15.0g        LABC           persistence of illness 4 in time period from 1987 to 1996


pil5w2            byte     %15.0g        LABC           persistence of illness 5 in time period from 1987 to 1996


pil6w2            byte     %15.0g        LABC           persistence of illness 6 in time period from 1987 to 1996


pil7w2            byte     %15.0g        LABC           persistence of illness 7 in time period from 1987 to 1996


pil8w2            byte     %15.0g        LABC           persistence of illness 8 in time period from 1987 to 1996


pil9w2            byte     %15.0g        LABC           persistence of illness 9 in time period from 1987 to 1996


pil10w2           byte     %15.0g        LABC           persistence of illness 10 in time period from 1987 to 1996


nil1w3            byte     %26.0g        ill862         name of illness 1 in time period now


nil2w3            byte     %26.0g        ill862         name of illness 2 in time period now


nil3w3            byte     %26.0g        ill862         name of illness 3 in time period now


nil4w3            byte     %26.0g        ill862         name of illness 4 in time period now


nil5w3            byte     %26.0g        ill862         name of illness 5 in time period now


nil6w3            byte     %26.0g        ill862         name of illness 6 in time period now


nil7w3            byte     %26.0g        ill862         name of illness 7 in time period now


nil8w3            byte     %26.0g        ill862         name of illness 8 in time period now


nil9w3            byte     %26.0g        ill862         name of illness 9 in time period now


nil10w3           byte     %26.0g        ill862         name of illness 10 in time period now


dil1w3            long     %d                            date of onset of illness 1 now


dil2w3            int      %d                            date of onset of illness 2 now


dil3w3            long     %d                            date of onset of illness 3 now


dil4w3            int      %d                            date of onset of illness 4 now


dil5w3            int      %d                            date of onset of illness 5 now


dil6w3            int      %d                            date of onset of illness 6 now


dil7w3            int      %d                            date of onset of illness 7 now


dil8w3            int      %d                            date of onset of illness 8 now


dil9w3            int      %d                            date of onset of illness 9 now


dil10w3           int      %d                            date of onset of illness 10 now


dril1w3           byte     %8.0g                        duration of illness 1 now (in years)


dril2w3           byte     %8.0g                        duration of illness 2 now (in years)


dril3w3           byte     %8.0g                        duration of illness 3 now (in years)


dril4w3           byte     %8.0g                        duration of illness 4 now (in years)


dril5w3           byte     %8.0g                        duration of illness 5 now (in years)


dril6w3           byte     %8.0g                        duration of illness 6 now (in years)


dril7w3           byte     %8.0g                        duration of illness 7 now (in years)


dril8w3           byte     %8.0g                        duration of illness 8 now (in years)


dril9w3           byte     %8.0g                        duration of illness 9 now (in years)


dril10w3          byte     %8.0g                        duration of illness 10 now (in years)


pil1w3            byte     %15.0g        LABC           persistence of illness 1 now


pil2w3            byte     %15.0g        LABC           persistence of illness 2 now


pil3w3            byte     %15.0g        LABC           persistence of illness 3 now


pil4w3            byte     %15.0g        LABC           persistence of illness 4 now


pil5w3            byte     %15.0g        LABC           persistence of illness 5 now


pil6w3            byte     %15.0g        LABC           persistence of illness 6 now


pil7w3            byte     %15.0g        LABC           persistence of illness 7 now


pil8w3            byte     %15.0g        LABC           persistence of illness 8 now


pil9w3            byte     %15.0g        LABC           persistence of illness 9 now


pil10w3           byte     %15.0g        LABC           persistence of illness 10 now


aborw1            byte     %8.0g                        number of pregnancy terminations in time period 1976-1986


aborw2            byte     %8.0g                        number of pregnancy terminations in time period 1987-1996


aborw3            byte     %8.0g                        number of pregnancy terminations in time period 1997-now


contw1            byte     %15.0g        LABC           use of any contraception method in 1976-1986


contw2            byte     %15.0g        LABC           use of any contraception method in 1987-1996


contw3            byte     %15.0g        LABC           use of any contraception method in 1997-now


ncontw1           byte     %15.0g        LABC           use of natural contraception in 1976-1986


ncontw2           byte     %15.0g        LABC           use of natural contraception in 1987-1996


ncontw3           byte     %15.0g        LABC           use of natural contraception in 1997-now


smokw1            int      %8.0g                        number of cigarettes per week  in 1976-1986


smokw2            int      %8.0g                        number of cigarettes per week  in 1987-1996


smokw3            int      %8.0g                        number of cigarettes per week in 1997-now


beerw1            byte     %8.0g                        nuber of beers per week in 1976-1986


beerw2            byte     %8.0g                        nuber of beers per week in 1987-1996


beerw3            byte     %8.0g                        nuber of beers per week in 1997-now


liqw1             byte     %8.0g                        number of spirits per week in 1976-1986


liqw2             byte     %8.0g                        number of spirits per week in 1987-1996


liqw3             byte     %8.0g                        number of spirits per week in 1997-now


pillw1            byte     %8.0g                        number of pills for pain per week in 1976-1986


pillw2            byte     %8.0g                        number of pills for pain per week in 1987-1996


pillw3            byte     %8.0g                        number of pills for pain per week in 1997-now


medcow1           byte     %8.0g                        number of medical visits  for a medical condition per year 1976-1986


medcow2           byte     %8.0g                        number of medical visits  for a medical condition per year 1987-1996


medcow3           byte     %8.0g                        number of medical visits for a medical condition per year 1997-now


hospw1            int      %8.0g                    *   number of days per year as a patient in a clinic for medical condition  in 1976-


hospw2            int      %8.0g                    *   number of days per year as a patient in a clinic for medical condition  in 1987-


hospw3            int      %8.0g                    *   number of days per year as a patient in a clinic for medical condition  in 1997-


vishphw1          byte     %8.0g                        number of visits per year to a homeopath for a physical condition in 1976-1986


vishphw2          byte     %8.0g                        number of visits per year to a homeopath for a physical condition in 1987-1996


vishphw3          byte     %8.0g                        number of visits per year to a homeopath for a physical condition in 1997-now


mhoutw1           byte     %8.0g                        number of medical visits  for a mental health condition per year 1976-1986


mhoutw2           byte     %8.0g                        number of medical visits  for a mental health condition  per year 1987-1996


mhoutw3           byte     %8.0g                        number of medical visits for a mental health condition per year 1997-now


mhinw1            byte     %8.0g                    *   number of days per year as a patient in a clinic for a mental health  in 1976-19


mhinw2            int      %8.0g                    *   number of days per year as a patient in a clinic for a mental health  in 1987-19


mhinw3            byte     %8.0g                    *   number of days per year as a patient in a clinic for a mental health  in 1997-no


vishpw1           byte     %8.0g                    *   number of visits per year to a homeopath for a mental health condition in 1976-1


vishpw2           byte     %8.0g                    *   number of visits per year to a homeopath for a mental health condition in 1987-1


vishpw3           byte     %8.0g                    *   number of visits per year to a homeopath for a mental health condition in 1997-n


goferw1           byte     %8.0g                        level of fear in percent from going outdoors in 1976-1986


goferw2           byte     %8.0g                        level of fear in percent from going outdoors in 1987-1996


goferw3           byte     %8.0g                        level of fear in percent from going outdoors in 1997-now


fdferw1           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 197


fdferw2           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 198


fdferw3           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 199


trgovw1           byte     %8.0g                        level of trust in government reports about chornobyl in time period 1976-1986


trgovw2           byte     %8.0g                        level of trust in government reports about chornobyl in time period 1987-1996


trgovw3           byte     %8.0g                        level of trust in government reports about chornobyl in time period 1997-now


trrepw1           byte     %8.0g                    *   level of trust in  medical/scientific reports about chornobyl in time period 197


trrepw2           byte     %8.0g                    *   level of trust in  medical/scientific reports about chornobyl in time period 198


trrepw3           byte     %8.0g                    *   level of trust in medical/scientific reports about chornobyl in time period 1997


townacc           str23    %23s                     *   village/ town/ city at time of accident


raiacc            str23    %23s                         raion at the time of Chornobyl accident


latacc            byte     %15.0g        LABF           latitude of residence at time of accident


lonacc            byte     %12.0g        lon            longitude of residence at time of accident


latdacc           byte     %8.0g                        latitude (in degrees) at time of accident


londacc           int      %8.0g                        longitude (in degrees) at time of accident


latmacc           byte     %8.0g                        latitude (in minutes) at time of accident


lonmacc           byte     %8.0g                        longitude (in minutes) at time of accident


oblacc            byte     %31.0g        LABG           oblast of residence at time of accident


kmacc             int      %8.0g                        distance of residence from the chornobyl plant (in kilometers)


townwork          str23    %23s                         village/town/ city of w/s at time of accident


rawork            str23    %23s                         raion of w/s at time of accident


latwork           byte     %15.0g        LABF           latitude of place of work/study at time of accident


lonwork           byte     %12.0g        lon            longitude of place of work/study at time of accident


latdwork          byte     %8.0g                        latitude (in degrees) of place of work/study at time of accident


londwork          int      %8.0g                        longitude (in degrees) of place of work/study at time of accident


latmwork          byte     %8.0g                        latitude (in minutes) of place of work/study at time of accident


lonmwork          byte     %8.0g                        longitude (in minutes) of place of work/study at time of accident


oblwork           byte     %31.0g        LABG           oblast of work /study at the time of accident


kmwork            int      %8.0g                    *   approximately how far away was your w/s from the chornobyl plant (in kilometers)


injself           byte     %15.0g        LABC           were you injured as a result of the chornobyl accident in 1986?


injselfr          byte     %9.0g         dum            Were u injured because of Chornobyl acc in 1986?


injoth            byte     %15.0g        LABC           was anyone you know injured as a result of the chornobyl accident?


injothr           byte     %9.0g         inj            Was anyone u know injured by Chornobyl accident?


evacself          byte     %15.0g        LABC           were you evacuated as a result of the chornobyl accident and its aftermath?


evacselfr         byte     %9.0g         dum            Were u evacuated because of Chornobyl accident in 1986?


relself           byte     %15.0g        LABC           were you relocated?


relselfr          byte     %9.0g         dum            Were u relocated because of Chornobyl accident?


townrel           str32    %32s                         village/ town/ city of relocated residence


rarel             str32    %32s                         raion of relocated residence


latrel            byte     %15.0g        LABF           latitude of relocated residence


lonrel            byte     %12.0g        lon            longitude of relocated residence


latdrel           byte     %8.0g                        latitude in degrees of relocated residence


londrel           byte     %8.0g                        longitude in degrees of relocated residence


latmrel           int      %8.0g                        latitude in minutes of relocated residence


lonmrel           int      %8.0g                        longitude in minutes of relocated residence


defnw1            byte     %8.0g                    *   consider hazardous (in percent) - deficiencies in essential nutrition in 1986


defnw2            byte     %8.0g                    *   consider hazardous (in percent) - deficiencies in essential nutrition in 1996


defnw3            byte     %8.0g                    *   consider hazardous (in percent) - deficiencies in essential nutrition NOW


efradw1           byte     %8.0g                        consider hazardous (in percent) - effects of radiation in 1986


efradw2           byte     %8.0g                        consider hazardous (in percent) - effects of radiation in 1996


efradw3           byte     %8.0g                        consider hazardous (in percent) - effects of radiation NOW


ecprw1            byte     %8.0g                        consider hazardous (in percent) - economic problems in 1986


ecprw2            byte     %8.0g                        consider hazardous (in percent) - economic problems in 1996


ecprw3            byte     %8.0g                        consider hazardous (in percent) - economic problems, NOW


polprw1           byte     %8.0g                        consider hazardous (in percent) - political problems in 1986


polprw2           byte     %8.0g                        consider hazardous (in percent) - political problems in 1996


polprw3           byte     %8.0g                        consider hazardous (in percent) - political problems NOW


airw1             byte     %8.0g                        consider hazardous (in percent) - air and water pollution in 1986


airw2             byte     %8.0g                        consider hazardous (in percent) - air and water pollution in 1996


airw3             byte     %8.0g                        consider hazardous (in percent) - air and water pollution NOW


radw1             byte     %8.0g                        believed % of the radioactively contaminated area  in 1986


radw2             byte     %8.0g                        believed % of the radioactively contaminated area in 1996


radw3             byte     %8.0g                        believed % of the radioactively contaminated area NOW


radchw1           byte     %8.0g                        believed % of polution related to chornobyl in 1986


radchw2           byte     %8.0g                        believed % of polution related to chornobyl in 1996


radchw3           byte     %8.0g                        believed % of polution related to chornobyl NOW


radtlw1           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime in 1986


radtlw2           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime in 1996


radtlw3           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime NOW


radhlw1           byte     %8.0g                        Self-perceived Chornobyl health threat in wave 1


radhlw2           byte     %8.0g                        how much believed personal health is affected by radiation in 1996


radhlw3           byte     %8.0g                        Self-perceived Chornobyl health threat in wave 3


radhlwc1          byte     %9.0g                        Collapsed version of radhlw1 with a cut point of 0-49=0 and 50-100=1


radhlwc2          byte     %9.0g                        Collapsed version of radhlw2 with a cut point of 0-49=0 and 50-100=1


radhlwc3          byte     %9.0g                        Collapsed version of radhlw1 with a cut point of 0-49=0 and 50-100=1


radfmw1           byte     %8.0g                        how much believed family health is affected by radiation in 1986


radfmw2           byte     %8.0g                        how much believed family health is affected by radiation in 1996


radfmw3           byte     %8.0g                        Observed


source            byte     %31.0g        q85        *   what was your initial source of information about the chornobyl plant accident?


dafter            int      %8.0g                    *   how many days lapsed after Chornobyl accident before you heard about the acciden


dauthw1           byte     %8.0g                        level of danger by authorities (in percent) in 1986


dauthw2           byte     %8.0g                        level of danger by authorities (in percent) in 1996


dauthw3           byte     %8.0g                        level of danger by authorities (in percent) NOW


medw1             byte     %8.0g                        level of danger by general media (in percent) in 1986


medw2             byte     %8.0g                        level of danger by general media (in percent) in 1996


medw3             byte     %8.0g                        level of danger by general media (in percent) NOW


neiw1             byte     %8.0g                        level of danger by neighbors (in percent) in 1986


neiw2             byte     %8.0g                        level of danger by neighbors (in percent) in 1996


neiw3             byte     %8.0g                        level of danger by neighbors (in percent) NOW


toxic             byte     %8.0g                        all radioactive materials remain toxic for thousands of years (% of agreement)


repair            byte     %8.0g                    *    body has capability to repair tissue damage caused by exposure (% of agreement)


skin              byte     %8.0g                        a suntan is caused by radiating damage to the skin (% of agreement)


near              byte     %8.0g                    *   radiation from a nuclear plant site is more concentrated near the plant (% of ag


cloud             byte     %8.0g                    *   radioactive fallout is only harmful when visible (% of agreement)


world             byte     %8.0g                    *   the chornobyl accident has affected people around the world (% of agreement)


healthef          byte     %8.0g                    *   a person exposed to any radiation  likely to suffer from (% of agreement)


carcin            byte     %8.0g                    *   a person exposed to carcinogen  is likely to get cancer (% of agreement)


woman             byte     %8.0g                    *   pregnant exposed to radiation likely to give birth to children with deffects (%


saferad           byte     %8.0g                        there is no safe level of radiation (% of agreement)


goodrad           byte     %8.0g                        small doses can actually improve one's health (% of agreement)


kzchorn           byte     %8.0g                    *   in k/z most cases of cancer in humans are known to be caused by radiation from


kzunder           byte     %8.0g                        people in k/z underestimate the risks assoicated with radiation (% of agreement)


chsize            byte     %8.0g                    *   the radioactive fallout from chornobyl affected more people than the radioactive


icdxcnt           byte     %9.0g                        count of icdx illnesses


icddx1            str32    %10s                         icd – 10 code illness 1


icddx2            str32    %10s                         icd – 10 code illness 2


icddx3            str32    %10s                         icd – 10 code illness 3


icddx4            str32    %10s                         icd – 10 code illness 4


icddx5            str32    %10s                         icd – 10 code illness 5


icddx6            str32    %10s                         icd – 10 code illness 6


icddx7            str32    %10s                         icd – 10 code illness 7


icddx8            str32    %10s                         icd – 10 code illness 8


icddx9            str32    %10s                         icd – 10 code illness 9


icddx10           str32    %10s                         icd – 10 code illness 10


icddx11           str32    %10s                         icd – 10 code illness 11


icddx12           str32    %10s                         icd – 10 code illness 12


dxdat_1           long     %d                           date of original onset (mm/dd/yyyy) illness 1


dxdat_2           int      %d                           date of original onset (mm/dd/yyyy) illness 2


dxdat_3           long     %d                           date of original onset (mm/dd/yyyy) illness 3


dxdat_4           long     %d                           date of original onset (mm/dd/yyyy) illness 4


dxdat_5           int      %d                           date of original onset (mm/dd/yyyy) illness 5


dxdat_6           int      %d                           date of original onset (mm/dd/yyyy) illness 6


dxdat_7           int      %d                           date of original onset (mm/dd/yyyy) illness 7


dxdat_8           int      %d                           date of original onset (mm/dd/yyyy) illness 8


dxdat_9           int      %d                           date of original onset (mm/dd/yyyy) illness 9


dxdat_10          int      %d                           date of original onset (mm/dd/yyyy) illness 10


dxdat_11          int      %d                           date of original onset (mm/dd/yyyy) illness 11


dxdat_12          int      %d                           date of original onset (mm/dd/yyyy) illness 12


dxnum1            byte     %8.0g                        number of years the desease persisted illness 1


dxnum2            byte     %8.0g                        number of years the desease persisted illness 2


dxnum3            byte     %8.0g                        number of years the desease persisted illness 3


dxnum4            byte     %8.0g                        number of years the desease persisted illness 4


dxnum5            byte     %8.0g                        number of years the desease persisted illness 5


dxnum6            byte     %8.0g                        number of years the desease persisted illness 6


dxnum7            byte     %8.0g                        number of years the desease persisted illness 7


dxnum8            byte     %8.0g                        number of years the desease persisted illness 8


dxnum9            byte     %8.0g                        number of years the desease persisted illness 9


dxnum10           byte     %8.0g                        number of years the desease persisted illness 10


dxnum11           byte     %8.0g                        number of years the desease persisted illness 11


dxnum12           byte     %8.0g                        number of years the desease persisted illness 12


deprl1980         byte     %8.0g                    *   level of depression (in percentage) in 1980


deprl1981         byte     %8.0g                        level of depression (in percentage) in 1981


deprl1982         byte     %8.0g                        level of depression (in percentage) in 1982


deprl1983         byte     %8.0g                        level of depression (in percentage) in 1983


deprl1984         byte     %8.0g                        level of depression (in percentage) in 1984


deprl1985         byte     %8.0g                        level of depression (in percentage) in 1985


deprl1986         byte     %8.0g                        level of depression (in percentage) in 1986


deprl1987         byte     %8.0g                        level of depression (in percentage) in 1987


deprl1988         byte     %8.0g                        level of depression (in percentage) in 1988


deprl1989         byte     %8.0g                        level of depression (in percentage) in 1989


deprl1990         byte     %8.0g                        level of depression (in percentage) in 1990


deprl1991         byte     %8.0g                        level of depression (in percentage) in 1991


deprl1992         byte     %8.0g                        level of depression (in percentage) in 1992


deprl1993         byte     %8.0g                        level of depression (in percentage) in 1993


deprl1994         byte     %8.0g                        level of depression (in percentage) in 1994


deprl1995         byte     %8.0g                        level of depression (in percentage) in 1995


deprl1996         byte     %8.0g                        level of depression (in percentage) in 1996


deprl1997         byte     %8.0g                        level of depression (in percentage) in 1997


deprl1998         byte     %8.0g                        level of depression (in percentage) in 1998


deprl1999         byte     %8.0g                        level of depression (in percentage) in 1999


deprl2000         byte     %8.0g                        level of depression (in percentage) in 2000


deprl2001         byte     %8.0g                        level of depression (in percentage) in 2001


deprl2002         byte     %8.0g                        level of depression (in percentage) in 2002


deprl2003         byte     %8.0g                        level of depression (in percentage) in 2003


deprl2004         byte     %8.0g                        level of depression (in percentage) in 2004


deprl2005         byte     %8.0g                        level of depression (in percentage) in 2005


deprl2006         byte     %8.0g                        level of depression (in percentage) in 2006


deprl2007         byte     %8.0g                        level of depression (in percentage) in 2007


deprl2008         byte     %8.0g                        level of depression (in percentage) in 2008


deprl2009         byte     %8.0g                        level of depression (in percentage) in 2009


deprl2010         byte     %8.0g                        level of depression (in percentage) in 2010


anxl1980          byte     %8.0g                        level of anxiety (in percentage) in 1980


anxl1981          byte     %8.0g                        level of anxiety (in percentage) in 1981


anxl1982          byte     %8.0g                        level of anxiety (in percentage) in 1982


anxl1983          byte     %8.0g                        level of anxiety (in percentage) in 1983


anxl1984          byte     %8.0g                        level of anxiety (in percentage) in 1984


anxl1985          byte     %8.0g                        level of anxiety (in percentage) in 1985


anxl1986          byte     %8.0g                        level of anxiety (in percentage) in 1986


anxl1987          byte     %8.0g                        level of anxiety (in percentage) in 1987


anxl1988          byte     %8.0g                        level of anxiety (in percentage) in 1988


anxl1989          byte     %8.0g                        level of anxiety (in percentage) in 1989


anxl1990          byte     %8.0g                        level of anxiety (in percentage) in 1990


anxl1991          byte     %8.0g                        level of anxiety (in percentage) in 1991


anxl1992          byte     %8.0g                        level of anxiety (in percentage) in 1992


anxl1993          byte     %8.0g                        level of anxiety (in percentage) in 1993


anxl1994          byte     %8.0g                        level of anxiety (in percentage) in 1994


anxl1995          byte     %8.0g                        level of anxiety (in percentage) in 1995


anxl1996          byte     %8.0g                        level of anxiety (in percentage) in 1996


anxl1997          byte     %8.0g                        level of anxiety (in percentage) in 1997


anxl1998          byte     %8.0g                        level of anxiety (in percentage) in 1998


anxl1999          byte     %8.0g                        level of anxiety (in percentage) in 1999


anxl2000          byte     %8.0g                        level of anxiety (in percentage) in 2000


anxl2001          byte     %8.0g                        level of anxiety (in percentage) in 2001


anxl2002          byte     %8.0g                        level of anxiety (in percentage) in 2002


anxl2003          byte     %8.0g                        level of anxiety (in percentage) in 2003


anxl2004          byte     %8.0g                        level of anxiety (in percentage) in 2004


anxl2005          byte     %8.0g                        level of anxiety (in percentage) in 2005


anxl2006          byte     %8.0g                        level of anxiety (in percentage) in 2006


anxl2007          byte     %8.0g                        level of anxiety (in percentage) in 2007


anxl2008          byte     %8.0g                        level of anxiety (in percentage) in 2008


anxl2009          byte     %8.0g                        level of anxiety (in percentage) in 2009


anxl2010          byte     %8.0g                        level of anxiety (in percentage) in 2010


pdisl1980         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1980


pdisl1981         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1981


pdisl1982         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1982


pdisl1983         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1983


pdisl1984         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1984


pdisl1985         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1985


pdisl1986         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1986


pdisl1987         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1987


pdisl1988         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1988


pdisl1989         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1989


pdisl1990         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1990


pdisl1991         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1991


pdisl1992         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1992


pdisl1993         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1993


pdisl1994         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1994


pdisl1995         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1995


pdisl1996         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1996


pdisl1997         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1997


pdisl1998         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1998


pdisl1999         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 1999


pdisl2000         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2000


pdisl2001         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2001


pdisl2002         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2002


pdisl2003         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2003


pdisl2004         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2004


pdisl2005         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2005


pdisl2006         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2006


pdisl2007         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2007


pdisl2008         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2008


pdisl2009         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2009


pdisl2010         byte     %8.0g                        level of somatic/physical discomforts (in percentage) in 2010


emrel1980         byte     %8.0g                        intensity of ptsd reactions in 1980


emrel1981         byte     %8.0g                        intensity of ptsd reactions in 1981


emrel1982         byte     %8.0g                        intensity of ptsd reactions in 1982


emrel1983         byte     %8.0g                        intensity of ptsd reactions in 1983


emrel1984         byte     %8.0g                        intensity of ptsd reactions in 1984


emrel1985         byte     %8.0g                        intensity of ptsd reactions in 1985


emrel1986         byte     %8.0g                        intensity of ptsd reactions in 1986


emrel1987         byte     %8.0g                        intensity of ptsd reactions in 1987


emrel1988         byte     %8.0g                        intensity of ptsd reactions in 1988


emrel1989         byte     %8.0g                        intensity of ptsd reactions in 1989


emrel1990         byte     %8.0g                        intensity of ptsd reactions in 1990


emrel1991         byte     %8.0g                        intensity of ptsd reactions in 1991


emrel1992         byte     %8.0g                        intensity of ptsd reactions in 1992


emrel1993         byte     %8.0g                        intensity of ptsd reactions in 1993


emrel1994         byte     %8.0g                        intensity of ptsd reactions in 1994


emrel1995         byte     %8.0g                        intensity of ptsd reactions in 1995


emrel1996         byte     %8.0g                        intensity of ptsd reactions in 1996


emrel1997         byte     %8.0g                        intensity of ptsd reactions in 1997


emrel1998         byte     %8.0g                        intensity of ptsd reactions in 1998


emrel1999         byte     %8.0g                        intensity of ptsd reactions in 1999


emrel2000         byte     %8.0g                        intensity of ptsd reactions in 2000


emrel2001         byte     %8.0g                        intensity of ptsd reactions in 2001


emrel2002         byte     %8.0g                        intensity of ptsd reactions in 2002


emrel2003         byte     %8.0g                        intensity of ptsd reactions in 2003


emrel2004         byte     %8.0g                        intensity of ptsd reactions in 2004


emrel2005         byte     %8.0g                        intensity of ptsd reactions in 2005


emrel2006         byte     %8.0g                        intensity of ptsd reactions in 2006


emrel2007         byte     %8.0g                        intensity of ptsd reactions in 2007


emrel2008         byte     %8.0g                        intensity of ptsd reactions in 2008


emrel2009         byte     %8.0g                        intensity of ptsd reactions in 2009


emrel2010         byte     %8.0g                        intensity of ptsd reactions in 2010


hlthl1980         byte     %8.0g                        intensity of work related problems due to health in 1980


hlthl1981         byte     %8.0g                        intensity of work related problems due to health in 1981


hlthl1982         byte     %8.0g                        intensity of work related problems due to health in 1982


hlthl1983         byte     %8.0g                        intensity of work related problems due to health in 1983


hlthl1984         byte     %8.0g                        intensity of work related problems due to health in 1984


hlthl1985         byte     %8.0g                        intensity of work related problems due to health in 1985


hlthl1986         byte     %8.0g                        intensity of work related problems due to health in 1986


hlthl1987         byte     %8.0g                        intensity of work related problems due to health in 1987


hlthl1988         byte     %8.0g                        intensity of work related problems due to health in 1988


hlthl1989         byte     %8.0g                        intensity of work related problems due to health in 1989


hlthl1990         byte     %8.0g                        intensity of work related problems due to health in 1990


hlthl1991         byte     %8.0g                        intensity of work related problems due to health in 1991


hlthl1992         byte     %8.0g                        intensity of work related problems due to health in 1992


hlthl1993         byte     %8.0g                        intensity of work related problems due to health in 1993


hlthl1994         byte     %8.0g                        intensity of work related problems due to health in 1994


hlthl1995         byte     %8.0g                        intensity of work related problems due to health in 1995


hlthl1996         byte     %8.0g                        intensity of work related problems due to health in 1996


hlthl1997         byte     %8.0g                        intensity of work related problems due to health in 1997


hlthl1998         byte     %8.0g                        intensity of work related problems due to health in 1998


hlthl1999         byte     %8.0g                        intensity of work related problems due to health in 1999


hlthl2000         byte     %8.0g                        intensity of work related problems due to health in 2000


hlthl2001         byte     %8.0g                        intensity of work related problems due to health in 2001


hlthl2002         byte     %8.0g                        intensity of work related problems due to health in 2002


hlthl2003         byte     %8.0g                        intensity of work related problems due to health in 2003


hlthl2004         byte     %8.0g                        intensity of work related problems due to health in 2004


hlthl2005         byte     %8.0g                        intensity of work related problems due to health in 2005


hlthl2006         byte     %8.0g                        intensity of work related problems due to health in 2006


hlthl2007         byte     %8.0g                        intensity of work related problems due to health in 2007


hlthl2008         byte     %8.0g                        intensity of work related problems due to health in 2008


hlthl2009         byte     %8.0g                        intensity of work related problems due to health in 2009


hlthl2010         byte     %8.0g                        intensity of work related problems due to health in 2010


homel1980         byte     %8.0g                    *   intensity of home related problems due to health in 1980


homel1981         byte     %8.0g                        intensity of home related problems due to health in 1981


homel1982         byte     %8.0g                        intensity of home related problems due to health in 1982


homel1983         byte     %8.0g                        intensity of home related problems due to health in 1983


homel1984         byte     %8.0g                        intensity of home related problems due to health in 1984


homel1985         byte     %8.0g                        intensity of home related problems due to health in 1985


homel1986         byte     %8.0g                        intensity of home related problems due to health in 1986


homel1987         byte     %8.0g                        intensity of home related problems due to health in 1987


homel1988         byte     %8.0g                        intensity of home related problems due to health in 1988


homel1989         byte     %8.0g                        intensity of home related problems due to health in 1989


homel1990         byte     %8.0g                        intensity of home related problems due to health in 1990


homel1991         byte     %8.0g                        intensity of home related problems due to health in 1991


homel1992         byte     %8.0g                        intensity of home related problems due to health in 1992


homel1993         byte     %8.0g                        intensity of home related problems due to health in 1993


homel1994         byte     %8.0g                        intensity of home related problems due to health in 1994


homel1995         byte     %8.0g                        intensity of home related problems due to health in 1995


homel1996         byte     %8.0g                        intensity of home related problems due to health in 1996


homel1997         byte     %8.0g                        intensity of home related problems due to health in 1997


homel1998         byte     %8.0g                        intensity of home related problems due to health in 1998


homel1999         byte     %8.0g                        intensity of home related problems due to health in 1999


homel2000         byte     %8.0g                        intensity of home related problems due to health in 2000


homel2001         byte     %8.0g                        intensity of home related problems due to health in 2001


homel2002         byte     %8.0g                        intensity of home related problems due to health in 2002


homel2003         byte     %8.0g                        intensity of home related problems due to health in 2003


homel2004         byte     %8.0g                        intensity of home related problems due to health in 2004


homel2005         byte     %8.0g                        intensity of home related problems due to health in 2005


homel2006         byte     %8.0g                        intensity of home related problems due to health in 2006


homel2007         byte     %8.0g                        intensity of home related problems due to health in 2007


homel2008         byte     %8.0g                        intensity of home related problems due to health in 2008


homel2009         byte     %8.0g                        intensity of home related problems due to health in 2009


homel2010         byte     %8.0g                        intensity of home related problems due to health in 2010


solil1980         byte     %8.0g                        intensity of social life related problems due to health in 1980


solil1981         byte     %8.0g                        intensity of social life related problems due to health in 1981


solil1982         byte     %8.0g                        intensity of social life related problems due to health in 1982


solil1983         byte     %8.0g                        intensity of social life related problems due to health in 1983


solil1984         byte     %8.0g                        intensity of social life related problems due to health in 1984


solil1985         byte     %8.0g                        intensity of social life related problems due to health in 1985


solil1986         byte     %8.0g                        intensity of social life related problems due to health in 1986


solil1987         byte     %8.0g                        intensity of social life related problems due to health in 1987


solil1988         byte     %8.0g                        intensity of social life related problems due to health in 1988


solil1989         byte     %8.0g                        intensity of social life related problems due to health in 1989


solil1990         byte     %8.0g                        intensity of social life related problems due to health in 1990


solil1991         byte     %8.0g                        intensity of social life related problems due to health in 1991


solil1992         byte     %8.0g                        intensity of social life related problems due to health in 1992


solil1993         byte     %8.0g                        intensity of social life related problems due to health in 1993


solil1994         byte     %8.0g                        intensity of social life related problems due to health in 1994


solil1995         byte     %8.0g                        intensity of social life related problems due to health in 1995


solil1996         byte     %8.0g                        intensity of social life related problems due to health in 1996


solil1997         byte     %8.0g                        intensity of social life related problems due to health in 1997


solil1998         byte     %8.0g                        intensity of social life related problems due to health in 1998


solil1999         byte     %8.0g                        intensity of social life related problems due to health in 1999


solil2000         byte     %8.0g                        intensity of social life related problems due to health in 2000


solil2001         byte     %8.0g                        intensity of social life related problems due to health in 2001


solil2002         byte     %8.0g                        intensity of social life related problems due to health in 2002


solil2003         byte     %8.0g                        intensity of social life related problems due to health in 2003


solil2004         byte     %8.0g                        intensity of social life related problems due to health in 2004


solil2005         byte     %8.0g                        intensity of social life related problems due to health in 2005


solil2006         byte     %8.0g                        intensity of social life related problems due to health in 2006


solil2007         byte     %8.0g                        intensity of social life related problems due to health in 2007


solil2008         byte     %8.0g                        intensity of social life related problems due to health in 2008


solil2009         byte     %8.0g                        intensity of social life related problems due to health in 2009


solil2010         byte     %8.0g                        intensity of social life related problems due to health in 2010


holil1980         byte     %8.0g                        intensity of home life related problems due to health in 1980


holil1981         byte     %8.0g                        intensity of home life related problems due to health in 1981


holil1982         byte     %8.0g                        intensity of home life related problems due to health in 1982


holil1983         byte     %8.0g                        intensity of home life related problems due to health in 1983


holil1984         byte     %8.0g                        intensity of home life related problems due to health in 1984


holil1985         byte     %8.0g                        intensity of home life related problems due to health in 1985


holil1986         byte     %8.0g                        intensity of home life related problems due to health in 1986


holil1987         byte     %8.0g                        intensity of home life related problems due to health in 1987


holil1988         byte     %8.0g                        intensity of home life related problems due to health in 1988


holil1989         byte     %8.0g                        intensity of home life related problems due to health in 1989


holil1990         byte     %8.0g                        intensity of home life related problems due to health in 1990


holil1991         byte     %8.0g                        intensity of home life related problems due to health in 1991


holil1992         byte     %8.0g                        intensity of home life related problems due to health in 1992


holil1993         byte     %8.0g                        intensity of home life related problems due to health in 1993


holil1994         byte     %8.0g                        intensity of home life related problems due to health in 1994


holil1995         byte     %8.0g                        intensity of home life related problems due to health in 1995


holil1996         byte     %8.0g                        intensity of home life related problems due to health in 1996


holil1997         byte     %8.0g                        intensity of home life related problems due to health in 1997


holil1998         byte     %8.0g                        intensity of home life related problems due to health in 1998


holil1999         byte     %8.0g                        intensity of home life related problems due to health in 1999


holil2000         byte     %8.0g                        intensity of home life related problems due to health in 2000


holil2001         byte     %8.0g                        intensity of home life related problems due to health in 2001


holil2002         byte     %8.0g                        intensity of home life related problems due to health in 2002


holil2003         byte     %8.0g                        intensity of home life related problems due to health in 2003


holil2004         byte     %8.0g                        intensity of home life related problems due to health in 2004


holil2005         byte     %8.0g                        intensity of home life related problems due to health in 2005


holil2006         byte     %8.0g                        intensity of home life related problems due to health in 2006


holil2007         byte     %8.0g                        intensity of home life related problems due to health in 2007


holil2008         byte     %8.0g                        intensity of home life related problems due to health in 2008


holil2009         byte     %8.0g                        intensity of home life related problems due to health in 2009


holil2010         byte     %8.0g                        intensity of home life related problems due to health in 2010


sexll1980         byte     %8.0g                        intensity of home life related problems due to health in 1980


sexll1981         byte     %8.0g                        intensity of home life related problems due to health in 1981


sexll1982         byte     %8.0g                        intensity of home life related problems due to health in 1982


sexll1983         byte     %8.0g                        intensity of home life related problems due to health in 1983


sexll1984         byte     %8.0g                        intensity of home life related problems due to health in 1984


sexll1985         byte     %8.0g                        intensity of home life related problems due to health in 1985


sexll1986         byte     %8.0g                        intensity of home life related problems due to health in 1986


sexll1987         byte     %8.0g                        intensity of home life related problems due to health in 1987


sexll1988         byte     %8.0g                        intensity of home life related problems due to health in 1988


sexll1989         byte     %8.0g                        intensity of home life related problems due to health in 1989


sexll1990         byte     %8.0g                        intensity of home life related problems due to health in 1990


sexll1991         byte     %8.0g                        intensity of home life related problems due to health in 1991


sexll1992         byte     %8.0g                        intensity of home life related problems due to health in 1992


sexll1993         byte     %8.0g                        intensity of home life related problems due to health in 1993


sexll1994         byte     %8.0g                        intensity of home life related problems due to health in 1994


sexll1995         byte     %8.0g                        intensity of home life related problems due to health in 1995


sexll1996         byte     %8.0g                        intensity of home life related problems due to health in 1996


sexll1997         byte     %8.0g                        intensity of home life related problems due to health in 1997


sexll1998         byte     %8.0g                        intensity of home life related problems due to health in 1998


sexll1999         byte     %8.0g                        intensity of home life related problems due to health in 1999


sexll2000         byte     %8.0g                        intensity of home life related problems due to health in 2000


sexll2001         byte     %8.0g                        intensity of home life related problems due to health in 2001


sexll2002         byte     %8.0g                        intensity of home life related problems due to health in 2002


sexll2003         byte     %8.0g                        intensity of home life related problems due to health in 2003


sexll2004         byte     %8.0g                        intensity of home life related problems due to health in 2004


sexll2005         byte     %8.0g                        intensity of home life related problems due to health in 2005


sexll2006         byte     %8.0g                        intensity of home life related problems due to health in 2006


sexll2007         byte     %8.0g                        intensity of home life related problems due to health in 2007


sexll2008         byte     %8.0g                        intensity of home life related problems due to health in 2008


sexll2009         byte     %8.0g                        intensity of home life related problems due to health in 2009


sexll2010         byte     %8.0g                        intensity of home life related problems due to health in 2010


inhol1980         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1980


inhol1981         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1981


inhol1982         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1982


inhol1983         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1983


inhol1984         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1984


inhol1985         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1985


inhol1986         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1986


inhol1987         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1987


inhol1988         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1988


inhol1989         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1989


inhol1990         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1990


inhol1991         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1991


inhol1992         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1992


inhol1993         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1993


inhol1994         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1994


inhol1995         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1995


inhol1996         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1996


inhol1997         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1997


inhol1998         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1998


inhol1999         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 1999


inhol2000         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2000


inhol2001         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2001


inhol2002         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2002


inhol2003         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2003


inhol2004         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2004


inhol2005         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2005


inhol2006         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2006


inhol2007         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2007


inhol2008         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2008


inhol2009         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2009


inhol2010         byte     %8.0g                        intensity of interest and hobbies related problems due to health in 2010


wendl1980         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1980


wendl1981         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1981


wendl1982         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1982


wendl1983         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1983


wendl1984         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1984


wendl1985         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1985


wendl1986         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1986


wendl1987         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1987


wendl1988         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1988


wendl1989         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1989


wendl1990         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1990


wendl1991         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1991


wendl1992         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1992


wendl1993         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1993


wendl1994         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1994


wendl1995         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1995


wendl1996         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1996


wendl1997         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1997


wendl1998         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1998


wendl1999         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 1999


wendl2000         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2000


wendl2001         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2001


wendl2002         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2002


wendl2003         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2003


wendl2004         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2004


wendl2005         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2005


wendl2006         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2006


wendl2007         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2007


wendl2008         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2008


wendl2009         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2009


wendl2010         byte     %8.0g                        intensity of holidays - weekends related problems due to health in 2010


smokel1980        int      %8.0g                        number of cigarettes smoked per week in 1980


smokel1981        int      %8.0g                        number of cigarettes smoked per week in 1981


smokel1982        int      %8.0g                        number of cigarettes smoked per week in 1982


smokel1983        int      %8.0g                        number of cigarettes smoked per week in 1983


smokel1984        int      %8.0g                        number of cigarettes smoked per week in 1984


smokel1985        int      %8.0g                        number of cigarettes smoked per week in 1985


smokel1986        int      %8.0g                        number of cigarettes smoked per week in 1986


smokel1987        int      %8.0g                        number of cigarettes smoked per week in 1987


smokel1988        int      %8.0g                        number of cigarettes smoked per week in 1988


smokel1989        int      %8.0g                        number of cigarettes smoked per week in 1989


smokel1990        int      %8.0g                        number of cigarettes smoked per week in 1990


smokel1991        int      %8.0g                        number of cigarettes smoked per week in 1991


smokel1992        int      %8.0g                        number of cigarettes smoked per week in 1992


smokel1993        int      %8.0g                        number of cigarettes smoked per week in 1993


smokel1994        int      %8.0g                        number of cigarettes smoked per week in 1994


smokel1995        int      %8.0g                        number of cigarettes smoked per week in 1995


smokel1996        int      %8.0g                        number of cigarettes smoked per week in 1996


smokel1997        int      %8.0g                        number of cigarettes smoked per week in 1997


smokel1998        int      %8.0g                        number of cigarettes smoked per week in 1998


smokel1999        int      %8.0g                        number of cigarettes smoked per week in 1999


smokel2000        int      %8.0g                        number of cigarettes smoked per week in 2000


smokel2001        int      %8.0g                        number of cigarettes smoked per week in 2001


smokel2002        int      %8.0g                        number of cigarettes smoked per week in 2002


smokel2003        int      %8.0g                        number of cigarettes smoked per week in 2003


smokel2004        int      %8.0g                        number of cigarettes smoked per week in 2004


smokel2005        int      %8.0g                        number of cigarettes smoked per week in 2005


smokel2006        int      %8.0g                        number of cigarettes smoked per week in 2006


smokel2007        int      %8.0g                        number of cigarettes smoked per week in 2007


smokel2008        int      %8.0g                        number of cigarettes smoked per week in 2008


smokel2009        int      %8.0g                        number of cigarettes smoked per week in 2009


smokel2010        int      %8.0g                        number of cigarettes smoked per week in 2010


drinl1980         byte     %8.0g                        number of beer of wine consumed per week in 1980


drinl1981         byte     %8.0g                        number of beer of wine consumed per week in 1981


drinl1982         byte     %8.0g                        number of beer of wine consumed per week in 1982


drinl1983         byte     %8.0g                        number of beer of wine consumed per week in 1983


drinl1984         byte     %8.0g                        number of beer of wine consumed per week in 1984


drinl1985         byte     %8.0g                        number of beer of wine consumed per week in 1985


drinl1986         byte     %8.0g                        number of beer of wine consumed per week in 1986


drinl1987         byte     %8.0g                        number of beer of wine consumed per week in 1987


drinl1988         byte     %8.0g                        number of beer of wine consumed per week in 1988


drinl1989         byte     %8.0g                        number of beer of wine consumed per week in 1989


drinl1990         byte     %8.0g                        number of beer of wine consumed per week in 1990


drinl1991         byte     %8.0g                        number of beer of wine consumed per week in 1991


drinl1992         byte     %8.0g                        number of beer of wine consumed per week in 1992


drinl1993         byte     %8.0g                        number of beer of wine consumed per week in 1993


drinl1994         byte     %8.0g                        number of beer of wine consumed per week in 1994


drinl1995         byte     %8.0g                        number of beer of wine consumed per week in 1995


drinl1996         byte     %8.0g                        number of beer of wine consumed per week in 1996


drinl1997         byte     %8.0g                        number of beer of wine consumed per week in 1997


drinl1998         byte     %8.0g                        number of beer of wine consumed per week in 1998


drinl1999         byte     %8.0g                        number of beer of wine consumed per week in 1999


drinl2000         byte     %8.0g                        number of beer of wine consumed per week in 2000


drinl2001         byte     %8.0g                        number of beer of wine consumed per week in 2001


drinl2002         byte     %8.0g                        number of beer of wine consumed per week in 2002


drinl2003         byte     %8.0g                        number of beer of wine consumed per week in 2003


drinl2004         byte     %8.0g                        number of beer of wine consumed per week in 2004


drinl2005         byte     %8.0g                        number of beer of wine consumed per week in 2005


drinl2006         byte     %8.0g                        number of beer of wine consumed per week in 2006


drinl2007         byte     %8.0g                        number of beer of wine consumed per week in 2007


drinl2008         byte     %8.0g                        number of beer of wine consumed per week in 2008


drinl2009         byte     %8.0g                        number of beer of wine consumed per week in 2009


drinl2010         byte     %8.0g                        number of beer of wine consumed per week in 2010


vodkaq1980        byte     %8.0g                        number of vodaka drinks consumed per week in 1980


vodkaq1981        byte     %8.0g                        number of vodaka drinks consumed per week in 1981


vodkaq1982        byte     %8.0g                        number of vodaka drinks consumed per week in 1982


vodkaq1983        byte     %8.0g                        number of vodaka drinks consumed per week in 1983


vodkaq1984        byte     %8.0g                        number of vodaka drinks consumed per week in 1984


vodkaq1985        byte     %8.0g                        number of vodaka drinks consumed per week in 1985


vodkaq1986        byte     %8.0g                        number of vodaka drinks consumed per week in 1986


vodkaq1987        byte     %8.0g                        number of vodaka drinks consumed per week in 1987


vodkaq1988        byte     %8.0g                        number of vodaka drinks consumed per week in 1988


vodkaq1989        byte     %8.0g                        number of vodaka drinks consumed per week in 1989


vodkaq1990        byte     %8.0g                        number of vodaka drinks consumed per week in 1990


vodkaq1991        byte     %8.0g                        number of vodaka drinks consumed per week in 1991


vodkaq1992        byte     %8.0g                        number of vodaka drinks consumed per week in 1992


vodkaq1993        byte     %8.0g                        number of vodaka drinks consumed per week in 1993


vodkaq1994        byte     %8.0g                        number of vodaka drinks consumed per week in 1994


vodkaq1995        byte     %8.0g                        number of vodaka drinks consumed per week in 1995


vodkaq1996        byte     %8.0g                        number of vodaka drinks consumed per week in 1996


vodkaq1997        byte     %8.0g                        number of vodaka drinks consumed per week in 1997


vodkaq1998        byte     %8.0g                        number of vodaka drinks consumed per week in 1998


vodkaq1999        byte     %8.0g                        number of vodaka drinks consumed per week in 1999


vodkaq2000        byte     %8.0g                        number of vodaka drinks consumed per week in 2000


vodkaq2001        byte     %8.0g                        number of vodaka drinks consumed per week in 2001


vodkaq2002        byte     %8.0g                        number of vodaka drinks consumed per week in 2002


vodkaq2003        byte     %8.0g                        number of vodaka drinks consumed per week in 2003


vodkaq2004        byte     %8.0g                        number of vodaka drinks consumed per week in 2004


vodkaq2005        byte     %8.0g                        number of vodaka drinks consumed per week in 2005


vodkaq2006        byte     %8.0g                        number of vodaka drinks consumed per week in 2006


vodkaq2007        byte     %8.0g                        number of vodaka drinks consumed per week in 2007


vodkaq2008        byte     %8.0g                        number of vodaka drinks consumed per week in 2008


vodkaq2009        byte     %8.0g                        number of vodaka drinks consumed per week in 2009


vodkaq2010        byte     %8.0g                        number of vodaka drinks consumed per week in 2010


painq1980         byte     %8.0g                        number of pain medications per week in 1980


painq1981         byte     %8.0g                        number of pain medications per week in 1981


painq1982         byte     %8.0g                        number of pain medications per week in 1982


painq1983         byte     %8.0g                        number of pain medications per week in 1983


painq1984         byte     %8.0g                        number of pain medications per week in 1984


painq1985         byte     %8.0g                        number of pain medications per week in 1985


painq1986         byte     %8.0g                        number of pain medications per week in 1986


painq1987         byte     %8.0g                        number of pain medications per week in 1987


painq1988         byte     %8.0g                        number of pain medications per week in 1988


painq1989         byte     %8.0g                        number of pain medications per week in 1989


painq1990         byte     %8.0g                        number of pain medications per week in 1990


painq1991         byte     %8.0g                        number of pain medications per week in 1991


painq1992         byte     %8.0g                        number of pain medications per week in 1992


painq1993         byte     %8.0g                        number of pain medications per week in 1993


painq1994         byte     %8.0g                        number of pain medications per week in 1994


painq1995         byte     %8.0g                        number of pain medications per week in 1995


painq1996         byte     %8.0g                        number of pain medications per week in 1996


painq1997         byte     %8.0g                        number of pain medications per week in 1997


painq1998         byte     %8.0g                        number of pain medications per week in 1998


painq1999         byte     %8.0g                        number of pain medications per week in 1999


painq2000         byte     %8.0g                        number of pain medications per week in 2000


painq2001         byte     %8.0g                        number of pain medications per week in 2001


painq2002         byte     %8.0g                        number of pain medications per week in 2002


painq2003         byte     %8.0g                        number of pain medications per week in 2003


painq2004         byte     %8.0g                        number of pain medications per week in 2004


painq2005         byte     %8.0g                        number of pain medications per week in 2005


painq2006         byte     %8.0g                        number of pain medications per week in 2006


painq2007         byte     %8.0g                        number of pain medications per week in 2007


painq2008         byte     %8.0g                        number of pain medications per week in 2008


painq2009         byte     %8.0g                        number of pain medications per week in 2009


painq2010         byte     %8.0g                        number of pain medications per week in 2010


doctn1980         byte     %8.0g                        number of doctor visits for any health reasons in 1980


doctn1981         byte     %8.0g                        number of doctor visits for any health reasons in 1981


doctn1982         byte     %8.0g                        number of doctor visits for any health reasons in 1982


doctn1983         byte     %8.0g                        number of doctor visits for any health reasons in 1983


doctn1984         byte     %8.0g                        number of doctor visits for any health reasons in 1984


doctn1985         byte     %8.0g                        number of doctor visits for any health reasons in 1985


doctn1986         byte     %8.0g                        number of doctor visits for any health reasons in 1986


doctn1987         byte     %8.0g                        number of doctor visits for any health reasons in 1987


doctn1988         byte     %8.0g                        number of doctor visits for any health reasons in 1988


doctn1989         byte     %8.0g                        number of doctor visits for any health reasons in 1989


doctn1990         byte     %8.0g                        number of doctor visits for any health reasons in 1990


doctn1991         byte     %8.0g                        number of doctor visits for any health reasons in 1991


doctn1992         byte     %8.0g                        number of doctor visits for any health reasons in 1992


doctn1993         byte     %8.0g                        number of doctor visits for any health reasons in 1993


doctn1994         byte     %8.0g                        number of doctor visits for any health reasons in 1994


doctn1995         byte     %8.0g                        number of doctor visits for any health reasons in 1995


doctn1996         byte     %8.0g                        number of doctor visits for any health reasons in 1996


doctn1997         byte     %8.0g                        number of doctor visits for any health reasons in 1997


doctn1998         byte     %8.0g                        number of doctor visits for any health reasons in 1998


doctn1999         byte     %8.0g                        number of doctor visits for any health reasons in 1999


doctn2000         byte     %8.0g                        number of doctor visits for any health reasons in 2000


doctn2001         byte     %8.0g                        number of doctor visits for any health reasons in 2001


doctn2002         byte     %8.0g                        number of doctor visits for any health reasons in 2002


doctn2003         byte     %8.0g                        number of doctor visits for any health reasons in 2003


doctn2004         byte     %8.0g                        number of doctor visits for any health reasons in 2004


doctn2005         byte     %8.0g                        number of doctor visits for any health reasons in 2005


doctn2006         byte     %8.0g                        number of doctor visits for any health reasons in 2006


doctn2007         byte     %8.0g                        number of doctor visits for any health reasons in 2007


doctn2008         byte     %8.0g                        number of doctor visits for any health reasons in 2008


doctn2009         byte     %8.0g                        number of doctor visits for any health reasons in 2009


doctn2010         byte     %8.0g                        number of doctor visits for any health reasons in 2010


fampll1980        byte     %8.0g                        percent of influence that radiation had on family planning in 1980


fampll1981        byte     %8.0g                        percent of influence that radiation had on family planning in 1981


fampll1982        byte     %8.0g                        percent of influence that radiation had on family planning in 1982


fampll1983        byte     %8.0g                        percent of influence that radiation had on family planning in 1983


fampll1984        byte     %8.0g                        percent of influence that radiation had on family planning in 1984


fampll1985        byte     %8.0g                        percent of influence that radiation had on family planning in 1985


fampll1986        byte     %8.0g                        percent of influence that radiation had on family planning in 1986


fampll1987        byte     %8.0g                        percent of influence that radiation had on family planning in 1987


fampll1988        byte     %8.0g                        percent of influence that radiation had on family planning in 1988


fampll1989        byte     %8.0g                        percent of influence that radiation had on family planning in 1989


fampll1990        byte     %8.0g                        percent of influence that radiation had on family planning in 1990


fampll1991        byte     %8.0g                        percent of influence that radiation had on family planning in 1991


fampll1992        byte     %8.0g                        percent of influence that radiation had on family planning in 1992


fampll1993        byte     %8.0g                        percent of influence that radiation had on family planning in 1993


fampll1994        byte     %8.0g                        percent of influence that radiation had on family planning in 1994


fampll1995        byte     %8.0g                        percent of influence that radiation had on family planning in 1995


fampll1996        byte     %8.0g                        percent of influence that radiation had on family planning in 1996


fampll1997        byte     %8.0g                        percent of influence that radiation had on family planning in 1997


fampll1998        byte     %8.0g                        percent of influence that radiation had on family planning in 1998


fampll1999        byte     %8.0g                        percent of influence that radiation had on family planning in 1999


fampll2000        byte     %8.0g                        percent of influence that radiation had on family planning in 2000


fampll2001        byte     %8.0g                        percent of influence that radiation had on family planning in 2001


fampll2002        byte     %8.0g                        percent of influence that radiation had on family planning in 2002


fampll2003        byte     %8.0g                        percent of influence that radiation had on family planning in 2003


fampll2004        byte     %8.0g                        percent of influence that radiation had on family planning in 2004


fampll2005        byte     %8.0g                        percent of influence that radiation had on family planning in 2005


fampll2006        byte     %8.0g                        percent of influence that radiation had on family planning in 2006


fampll2007        byte     %8.0g                        percent of influence that radiation had on family planning in 2007


fampll2008        byte     %8.0g                        percent of influence that radiation had on family planning in 2008


fampll2009        byte     %8.0g                        percent of influence that radiation had on family planning in 2009


fampll2010        byte     %8.0g                        percent of influence that radiation had on family planning in 2010


sett1r1           str23    %23s                     *   town of residence 1 time: april 26 - june 30 1986


sett1r2           str32    %32s                     *   town of residence 2 time: april 26 - june 30 1986


sett1r3           str32    %32s                     *   town of residence 3 time: april 26 - june 30 1986


sett1r4           str32    %32s                     *   town of residence 4 time: april 26 - june 30 1986


rait1r1           str23    %23s                     *   raion of residence 1 time: april 26 - june 30 1986


rait1r2           str32    %32s                     *   raion of residence 2 time: april 26 - june 30 1986


rait1r3           str32    %32s                     *   raion of residence 3 time: april 26 - june 30 1986


rait1r4           str32    %32s                     *   raion of residence 4 time: april 26 - june 30 1986


latdt1r1          byte     %10.0g                   *   latitude in degrees residence 1 time 1 april 26-june 30 1986


latdt1r2          byte     %10.0g                   *   latitude in degrees residence 2 time 1 april 26-june 30 1986


latdt1r3          byte     %10.0g                   *   latitude in degrees residence 3 time 1 april 26-june 30 1986


latdt1r4          byte     %10.0g                   *   latitude in degrees residence 4 time 1 april 26-june 30 1986


londt1r1          int      %10.0g                   *   longitude in degrees residence 1 time 1 april 26-june 30 1986


londt1r2          int      %10.0g                   *   longitude in degrees residence 2 time 1 april 26-june 30 1986


londt1r3          byte     %10.0g                   *   longitude in degrees residence 3 time 1 april 26-june 30 1986


londt1r4          byte     %10.0g                   *   longitude in degrees residence 4 time 1 april 26-june 30 1986


latmt1r1          byte     %10.0g                   *   latitude in minutes residence 1 time 1 april 26-june 30 1986


latmt1r2          int      %10.0g                   *   latitude in minutes residence 2 time 1 april 26-june 30 1986


latmt1r3          byte     %10.0g                   *   latitude in minutes residence 3 time 1 april 26-june 30 1986


latmt1r4          byte     %10.0g                   *   latitude in minutes residence 4 time 1 april 26-june 30 1986


lonmt1r1          byte     %10.0g                   *   longitude in minutes residence 1 time 1 april 26-june 30 1986


lonmt1r2          int      %10.0g                   *   longitude in minutes residence 2 time 1 april 26-june 30 1986


lonmt1r3          byte     %10.0g                   *   longitude in minutes residence 3 time 1 april 26-june 30 1986


lonmt1r4          byte     %10.0g                   *   longitude in minutes residence 4 time 1 april 26-june 30 1986


dayt1r1           int      %10.0g                   *   days in residence 1 time 1 april 26-june 30 1986


dayt1r2           byte     %10.0g                   *   days in residence 2 time 1 april 26-june 30 1986


dayt1r3           byte     %10.0g                   *   days in residence 3 time 1 april 26-june 30 1986


dayt1r4           byte     %10.0g                   *   days in residence 4 time 1 april 26-june 30 1986


oblt1r1           byte     %31.0g        LABG       *   oblast of residence 1 time 1 april 26-june 30 1986


oblt1r2           byte     %31.0g        LABG       *   oblast of residence 2 time 1 april 26-june 30 1986


oblt1r3           byte     %31.0g        LABG       *   oblast of residence 3 time 1 april 26-june 30 1986


oblt1r4           byte     %31.0g        LABG       *   oblast of residence 4 time 1 april 26-june 30 1986


latt1r1           byte     %15.0g        LABF       *   latitude direction residence 1 time 1 april 26-june 30 1986


latt1r2           byte     %15.0g        LABF       *   latitude direction residence 2 time 1 april 26-june 30 1986


latt1r3           byte     %15.0g        LABF       *   latitude direction residence 3 time 1 april 26-june 30 1986


latt1r4           byte     %15.0g        LABF       *   latitude direction residence 4 time 1 april 26-june 30 1986


lont1r1           byte     %10.0g        lon        *   longitude direction residence 1 time 1 april 26-june 30 1986


lont1r2           byte     %10.0g        lon        *   longitude direction residence 2 time 1 april 26-june 30 1986


lont1r3           byte     %10.0g        lon        *   longitude direction residence 3 time 1 april 26-june 30 1986


lont1r4           byte     %10.0g        lon        *   longitude direction residence 4 time 1 april 26-june 30 1986


typet1r1          byte     %23.0g        LABL       *   type of residence 1 time 1 april 26-june 30 1986


typet1r2          byte     %23.0g        LABL       *   type of residence 2 time 1 april 26-june 30 1986


typet1r3          byte     %23.0g        LABL       *   type of residence 3 time 1 april 26-june 30 1986


typet1r4          byte     %23.0g        LABL       *   type of residence 4 time 1 april 26-june 30 1986


occt1r1           byte     %22.0g        LABM       *   occupation while in residence 1 time 1 april 26-june 30 1986


occt1r2           byte     %22.0g        LABM       *   occupation while in residence 2 time 1 april 26-june 30 1986


occt1r3           byte     %22.0g        LABM       *   occupation while in residence 3 time 1 april 26-june 30 1986


occt1r4           byte     %22.0g        LABM       *   occupation while in residence 1 time 1 april 26-june 30 1986


ldrt1r1           byte     %15.0g        LABC       *   did you consume liquid dairy products while in residence 1 time 1


ldrt1r2           byte     %15.0g        LABC       *   did you consume liquid dairy products while in residence 2 time 1


ldrt1r3           byte     %15.0g        LABC       *   did you consume liquid dairy products while in residence 3 time 1


ldrt1r4           byte     %15.0g        LABC       *   did you consume liquid dairy products while in residence 4 time 1


sldrt1r1          byte     %20.0g        LABN       *   source of liquid dairy products while in residence 1 time 1


sldrt1r2          byte     %20.0g        LABN       *   source of liquid dairy products while in residence 2 time 1


sldrt1r3          byte     %20.0g        LABN       *   source of liquid dairy products while in residence 3 time 1


sldrt1r4          byte     %20.0g        LABN       *   source of liquid dairy products while in residence 4 time 1


mlldt1r1          long     %8.0g                    *   quantity of liquid dairy products (in ml) while in residence 1 time 1


mlldt1r2          int      %8.0g                    *   quantity of liquid dairy products (in ml) while in residence 2 time 1


mlldt1r3          int      %8.0g                    *   quantity of liquid dairy products (in ml) while in residence 3 time 1


mlldt1r4          int      %8.0g                    *   quantity of liquid dairy products (in ml) while in residence 4 time 1


sdrt1r1           byte     %15.0g        LABC       *   did you consume solid dairy products while in residence 1 time 1


sdrt1r2           byte     %15.0g        LABC       *   did you consume solid dairy products while in residence 2 time 1


sdrt1r3           byte     %15.0g        LABC       *   did you consume solid dairy products while in residence 3 time 1


sdrt1r4           byte     %15.0g        LABC       *   did you consume solid dairy products while in residence 4 time 1


ssdrt1r1          byte     %20.0g        LABN       *   sourse of solid dairy products in residence 1 time 1


ssdrt1r2          byte     %20.0g        LABN       *   sourse of solid dairy products in residence 2 time 1


ssdrt1r3          byte     %20.0g        LABN       *   sourse of solid dairy products in residence 3 time 1


ssdrt1r4          byte     %20.0g        LABN       *   sourse of solid dairy products in residence 4 time 1


gldt1r1           long     %8.0g                    *   quantity of solid dairy products (in grams) while in residence 1 time 1


gldt1r2           long     %8.0g                    *   quantity of solid dairy products (in grams) while in residence 2 time 1


gldt1r3           int      %8.0g                    *   quantity of solid dairy products (in grams) while in residence 3 time 1


gldt1r4           int      %8.0g                    *   quantity of solid dairy products (in grams) while in residence 4 time 1


lvt1r1            byte     %15.0g        LABC       *   did you consume leafy vegetables while in residence 1 time 1


lvt1r2            byte     %15.0g        LABC       *   did you consume leafy vegetables while in residence 2 time 1


lvt1r3            byte     %15.0g        LABC       *   did you consume leafy vegetables while in residence 3 time 1


lvt1r4            byte     %15.0g        LABC       *   did you consume leafy vegetables while in residence 4 time 1


slvt1r1           byte     %20.0g        LABN       *   source of leafy vegetables while in residence 1 time 1


slvt1r2           byte     %20.0g        LABN       *   source of leafy vegetables while in residence 2 time 1


slvt1r3           byte     %20.0g        LABN       *   source of leafy vegetables while in residence 3 time 1


slvt1r4           byte     %20.0g        LABN       *   source of leafy vegetables while in residence 4 time 1


glvt1r1           int      %8.0g                    *   quantity of leafy vegetables (in grams) while in residence 1 time 1


glvt1r2           int      %8.0g                    *   quantity of leafy vegetables (in grams) while in residence 2 time 1


glvt1r3           int      %8.0g                    *   quantity of leafy vegetables (in grams) while in residence 3 time 1


glvt1r4           int      %8.0g                    *   quantity of leafy vegetables (in grams) while in residence 4 time 1


sett2r1           str23    %23s                     *   town of residence 1 time2: july 1- december 31 1986


sett2r2           str32    %32s                     *   town of residence 2 time2: july 1- december 31 1986


sett2r3           str32    %32s                     *   town of residence 3 time2: july 1- december 31 1986


sett2r4           str32    %32s                     *   town of residence 4 time2: july 1- december 31 1986


rait2r1           str23    %23s                     *   raion of residence 1 time2: july 1- december 31 1986


rait2r2           str32    %32s                     *   raion of residence 2 time2: july 1- december 31 1986


rait2r3           str32    %32s                     *   raion of residence 3 time2: july 1- december 31 1986


rait2r4           str32    %32s                     *   raion of residence 4 time2: july 1- december 31 1986


latdt2r1          byte     %8.0g                    *   latitude in degrees residence 1 time 2:  july 1-december 31 1986


latdt2r2          byte     %8.0g                    *   latitude in degrees residence 2 time 2:  july 1-december 31 1986


latdt2r3          byte     %8.0g                    *   latitude in degrees residence 3 time 2:  july 1-december 31 1986


latdt2r4          byte     %8.0g                    *   latitude in degrees residence 4 time 2:  july 1-december 31 1986


londt2r1          byte     %8.0g                    *   longitude in degrees residence 1 time 2:  july 1-december 31 1986


londt2r2          byte     %8.0g                    *   longitude in degrees residence 2 time 2:  july 1-december 31 1986


londt2r3          byte     %8.0g                    *   longitude in degrees residence 3 time 2:  july 1-december 31 1986


londt2r4          byte     %8.0g                    *   longitude in degrees residence 4 time 2:  july 1-december 31 1986


latmt2r1          byte     %8.0g                    *   latitude in minutes residence 1 time 2:  july 1-december 31 1986


latmt2r2          byte     %8.0g                    *   latitude in minutes residence 2 time 2:  july 1-december 31 1986


latmt2r3          byte     %8.0g                    *   latitude in minutes residence 3 time 2:  july 1-december 31 1986


latmt2r4          byte     %8.0g                    *   latitude in minutes residence 4 time 2:  july 1-december 31 1986


lonmt2r1          byte     %8.0g                    *   longitude in minutes residence 1 time 2:  july 1-december 31 1986


lonmt2r2          byte     %8.0g                    *   longitude in minutes residence 2 time 2:  july 1-december 31 1986


lonmt2r3          byte     %8.0g                    *   longitude in minutes residence 3 time 2:  july 1-december 31 1986


lonmt2r4          byte     %8.0g                    *   longitude in minutes residence 4 time 2:  july 1-december 31 1986


dayt2r1           int      %10.0g                   *   days in residence 1 time 2: from july 1 -december 31 1986


dayt2r2           int      %10.0g                   *   days in residence 2 time 2: from july 1 -december 31 1986


dayt2r3           int      %10.0g                   *   days in residence 3 time 2: from july 1 -december 31 1986


dayt2r4           int      %10.0g                   *   days in residence 4 time 2: from july 1 -december 31 1986


oblt2r1           byte     %31.0g        LABG       *   oblast of residence 1 time 2:  july 1-december 31 1986


oblt2r2           byte     %31.0g        LABG       *   oblast of residence 2 time 2:  july 1-december 31 1986


oblt2r3           byte     %31.0g        LABG       *   oblast of residence 3 time 2:  july 1-december 31 1986


oblt2r4           byte     %31.0g        LABG       *   oblast of residence 4 time 2:  july 1-december 31 1986


latt2r1           byte     %15.0g        LABF       *   latitude direction of residence 1 time 2:  july 1-december 31 1986


latt2r2           byte     %15.0g        LABF       *   latitude direction of residence 2 time 2:  july 1-december 31 1986


latt2r3           byte     %15.0g        LABF       *   latitude direction of residence 3 time 2:  july 1-december 31 1986


latt2r4           byte     %15.0g        LABF       *   latitude direction of residence 4 time 2:  july 1-december 31 1986


lont2r1           byte     %10.0g        lon        *   longitude direction of residence 1 time 2:  july 1-december 31 1986


lont2r2           byte     %10.0g        lon        *   longitude direction of residence 2 time 2:  july 1-december 31 1986


lont2r3           byte     %10.0g        lon        *   longitude direction of residence 3 time 2:  july 1-december 31 1986


lont2r4           byte     %10.0g        lon        *   longitude direction of residence 4 time 2:  july 1-december 31 1986


typet2r1          byte     %23.0g        LABL       *   type of residence 1 time 2:  july 1-december 31 1986


typet2r2          byte     %23.0g        LABL       *   type of residence 2 time 2:  july 1-december 31 1986


typet2r3          byte     %23.0g        LABL       *   type of residence 3 time 2:  july 1-december 31 1986


typet2r4          byte     %23.0g        LABL       *   type of residence 4 time 2:  july 1-december 31 1986


occt2r1           byte     %22.0g        LABM       *   occupation when in residence 1 time 2:  july 1-december 31 1986


occt2r2           byte     %22.0g        LABM       *   occupation when in residence 2 time 2:  july 1-december 31 1986


occt2r3           byte     %22.0g        LABM       *   occupation when in residence 3 time 2:  july 1-december 31 1986


occt2r4           byte     %22.0g        LABM       *   occupation when in residence 4 time 2:  july 1-december 31 1986


ldrt2r1           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 1 time 2:  july 1-december 31 1986


ldrt2r2           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 2 time 2:  july 1-december 31 1986


ldrt2r3           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 3 time 2:  july 1-december 31 1986


ldrt2r4           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 4 time 2:  july 1-december 31 1986


sldrt2r1          byte     %20.0g        LABN       *   source of liquid dairy residence 1 time 2:  july 1-december 31 1986


sldrt2r2          byte     %20.0g        LABN       *   source of liquid dairy residence 2 time 2:  july 1-december 31 1986


sldrt2r3          byte     %20.0g        LABN       *   source of liquid dairy residence 3 time 2:  july 1-december 31 1986


sldrt2r4          byte     %20.0g        LABN       *   source of liquid dairy residence 4 time 2:  july 1-december 31 1986


mlldt2r1          int      %8.0g                    *   quantity liquid dairy (in ml) residence 1 time 2:  july 1-december 31 1986


mlldt2r2          int      %8.0g                    *   quantity liquid dairy (in ml) residence 2 time 2:  july 1-december 31 1986


mlldt2r3          int      %8.0g                    *   quantity liquid dairy (in ml) residence 3 time 2:  july 1-december 31 1986


mlldt2r4          int      %8.0g                    *   quantity liquid dairy (in ml) residence 4 time 2:  july 1-december 31 1986


sdrt2r1           byte     %15.0g        LABC       *   did you consume solid dairy in residence 1 time 2:  july 1-december 31 1986


sdrt2r2           byte     %15.0g        LABC       *   did you consume solid dairy in residence 2 time 2:  july 1-december 31 1986


sdrt2r3           byte     %15.0g        LABC       *   did you consume solid dairy in residence 3 time 2:  july 1-december 31 1986


sdrt2r4           byte     %15.0g        LABC       *   did you consume solid dairy in residence 4 time 2:  july 1-december 31 1986


ssdrt2r1          byte     %20.0g        LABN       *   source of solid dairy in residence 1 time 2:  july 1-december 31 1986


ssdrt2r2          byte     %20.0g        LABN       *   source of solid dairy in residence 2 time 2:  july 1-december 31 1986


ssdrt2r3          byte     %20.0g        LABN       *   source of solid dairy in residence 3 time 2:  july 1-december 31 1986


ssdrt2r4          byte     %20.0g        LABN       *   source of solid dairy in residence 4 time 2:  july 1-december 31 1986


gldt2r1           long     %8.0g                    *   quantity solid dairy (in grams) residence 1 time 2:  july 1-december 31 1986


gldt2r2           long     %8.0g                    *   quantity solid dairy (in grams) residence 2 time 2:  july 1-december 31 1986


gldt2r3           int      %8.0g                    *   quantity solid dairy (in grams) residence 3 time 2:  july 1-december 31 1986


gldt2r4           int      %8.0g                    *   quantity solid dairy (in grams) residence 4 time 2:  july 1-december 31 1986


pott2r1           byte     %15.0g        LABC           did you consume potatoes  in residence 1 time 2:  july 1-december 31 1986


pott2r2           byte     %15.0g        LABC           did you consume potatoes  in residence 2 time 2:  july 1-december 31 1986


pott2r3           byte     %15.0g        LABC           did you consume potatoes  in residence 3 time 2:  july 1-december 31 1986


pott2r4           byte     %15.0g        LABC           did you consume potatoes  in residence 4 time 2:  july 1-december 31 1986


spott2r1          byte     %20.0g        LABN           source of potatoes  in residence 1 time 2:  july 1-december 31 1986


spott2r2          byte     %20.0g        LABN           source of potatoes  in residence 2 time 2:  july 1-december 31 1986


spott2r3          byte     %20.0g        LABN           source of potatoes  in residence 3 time 2:  july 1-december 31 1986


spott2r4          byte     %20.0g        LABN           source of potatoes  in residence 4 time 2:  july 1-december 31 1986


gpott2r1          long     %8.0g                    *   quantity of potatoes (in grams) in residence 1 time 2:  july 1-december 31 1986


gpott2r2          long     %8.0g                    *   quantity of potatoes (in grams) in residence 2 time 2:  july 1-december 31 1986


gpott2r3          int      %8.0g                    *   quantity of potatoes (in grams) in residence 3 time 2:  july 1-december 31 1986


gpott2r4          int      %8.0g                    *   quantity of potatoes (in grams) in residence 4 time 2:  july 1-december 31 1986


prkt2r1           byte     %15.0g        LABC           did you consume pork  in residence 1 time 2:  july 1-december 31 1986


prkt2r2           byte     %15.0g        LABC           did you consume pork  in residence 2 time 2:  july 1-december 31 1986


prkt2r3           byte     %15.0g        LABC           did you consume pork  in residence 3 time 2:  july 1-december 31 1986


prkt2r4           byte     %15.0g        LABC           did you consume pork  in residence 4 time 2:  july 1-december 31 1986


sprkt2r1          byte     %20.0g        LABN           source of pork  in residence 1 time 2:  july 1-december 31 1986


sprkt2r2          byte     %20.0g        LABN           source of pork  in residence 2 time 2:  july 1-december 31 1986


sprkt2r3          byte     %20.0g        LABN           source of pork  in residence 3 time 2:  july 1-december 31 1986


sprkt2r4          byte     %20.0g        LABN           source of pork  in residence 4 time 2:  july 1-december 31 1986


gprkt2r1          int      %8.0g                    *   quantity of pork (in grams) residence 1 time 2:  july 1-december 31 1986


gprkt2r2          int      %8.0g                    *   quantity of pork (in grams) residence 2 time 2:  july 1-december 31 1986


gprkt2r3          int      %8.0g                    *   quantity of pork (in grams) residence 3 time 2:  july 1-december 31 1986


gprkt2r4          int      %8.0g                    *   quantity of pork (in grams) residence 4 time 2:  july 1-december 31 1986


beft2r1           byte     %15.0g        LABC           did you consume beef  in residence 1 time 2:  july 1-december 31 1986


beft2r2           byte     %15.0g        LABC           did you consume beef  in residence 2 time 2:  july 1-december 31 1986


beft2r3           byte     %15.0g        LABC           did you consume beef  in residence 3 time 2:  july 1-december 31 1986


beft2r4           byte     %15.0g        LABC           did you consume beef  in residence 4 time 2:  july 1-december 31 1986


sbeft2r1          byte     %20.0g        LABN           source of beef  in residence 1 time 2:  july 1-december 31 1986


sbeft2r2          byte     %20.0g        LABN           source of beef  in residence 2 time 2:  july 1-december 31 1986


sbeft2r3          byte     %20.0g        LABN           source of beef  in residence 3 time 2:  july 1-december 31 1986


sbeft2r4          byte     %20.0g        LABN           source of beef  in residence 4 time 2:  july 1-december 31 1986


gbeft2r1          int      %8.0g                    *   quantity of beef (in grams)  residence 1 time 2:  july 1-december 31 1986


gbeft2r2          int      %8.0g                    *   quantity of beef (in grams)  residence 2 time 2:  july 1-december 31 1986


gbeft2r3          int      %8.0g                    *   quantity of beef (in grams)  residence 3 time 2:  july 1-december 31 1986


gbeft2r4          int      %8.0g                    *   quantity of beef (in grams)  residence 4 time 2:  july 1-december 31 1986


pltt2r1           byte     %15.0g        LABC           did you consume poultry  in residence 1 time 2:  july 1-december 31 1986


pltt2r2           byte     %15.0g        LABC           did you consume poultry  in residence 2 time 2:  july 1-december 31 1986


pltt2r3           byte     %15.0g        LABC           did you consume poultry  in residence 3 time 2:  july 1-december 31 1986


pltt2r4           byte     %15.0g        LABC           did you consume poultry  in residence 4 time 2:  july 1-december 31 1986


spltt2r1          byte     %20.0g        LABN           source of poultry  in residence 1 time 2:  july 1-december 31 1986


spltt2r2          byte     %20.0g        LABN           source of poultry  in residence 2 time 2:  july 1-december 31 1986


spltt2r3          byte     %20.0g        LABN           source of poultry  in residence 3 time 2:  july 1-december 31 1986


spltt2r4          byte     %20.0g        LABN           source of poultry  in residence 4 time 2:  july 1-december 31 1986


gpltt2r1          int      %8.0g                    *   quantity of poultry (in grams) in residence 1 time 2:  july 1-december 31 1986


gpltt2r2          int      %8.0g                    *   quantity of poultry (in grams) in residence 2 time 2:  july 1-december 31 1986


gpltt2r3          int      %8.0g                    *   quantity of poultry (in grams) in residence 3 time 2:  july 1-december 31 1986


gpltt2r4          int      %8.0g                    *   quantity of poultry (in grams) in residence 4 time 2:  july 1-december 31 1986


msht2r1           byte     %15.0g        LABC           did you consume mushrooms  in residence 1 time 2:  july 1-december 31 1986


msht2r2           byte     %15.0g        LABC           did you consume mushrooms  in residence 2 time 2:  july 1-december 31 1986


msht2r3           byte     %15.0g        LABC           did you consume mushrooms  in residence 3 time 2:  july 1-december 31 1986


msht2r4           byte     %15.0g        LABC           did you consume mushrooms  in residence 4 time 2:  july 1-december 31 1986


smsht2r1          byte     %20.0g        LABN           source of mushrooms in residence 1 time 2:  july 1-december 31 1986


smsht2r2          byte     %20.0g        LABN           source of mushrooms in residence 2 time 2:  july 1-december 31 1986


smsht2r3          byte     %20.0g        LABN           source of mushrooms in residence 3 time 2:  july 1-december 31 1986


smsht2r4          byte     %20.0g        LABN           source of mushrooms in residence 4 time 2:  july 1-december 31 1986


gmsht2r1          int      %8.0g                    *   quantity of mushr (in grams) per week residence 1 time 2:  july1-december 31


gmsht2r2          int      %8.0g                    *   quantity of mushr (in grams) per week residence 2 time 2:  july1-december 31


gmsht2r3          int      %8.0g                    *   quantity of mushr (in grams) per week residence 3 time 2:  july1-december 31


gmsht2r4          byte     %8.0g                    *   quantity of mushr (in grams) per week residence 4 time 2:  july1-december 31


sett3r1           str23    %23s                     *   town of residence 1 time 3: jan 1987 - dec 1990


sett3r2           str32    %32s                     *   town of residence 2 time 3: jan 1987 - dec 1990


sett3r3           str32    %32s                     *   town of residence 3 time 3: jan 1987 - dec 1990


sett3r4           str32    %32s                     *   town of residence 4 time 3: jan 1987 - dec 1990


rait3r1           str23    %23s                     *   raion of residence 1 time 3: jan 1987 - dec 1990


rait3r2           str32    %32s                     *   raion of residence 2 time 3: jan 1987 - dec 1990


rait3r3           str32    %32s                     *   raion of residence 3 time 3: jan 1987 - dec 1990


rait3r4           str32    %32s                     *   raion of residence 4 time 3: jan 1987 - dec 1990


latdt3r1          byte     %8.0g                    *   latitude in degrees residence 1 time 3: jan 1987 - dec 1990


latdt3r2          byte     %8.0g                    *   latitude in degrees residence 2 time 3: jan 1987 - dec 1990


latdt3r3          byte     %8.0g                    *   latitude in degrees residence 3 time 3: jan 1987 - dec 1990


latdt3r4          byte     %8.0g                    *   latitude in degrees residence 4 time 3: jan 1987 - dec 1990


londt3r1          int      %8.0g                    *   longitude in degrees residence 1 time 3: jan 1987 - dec 1990


londt3r2          int      %8.0g                    *   longitude in degrees residence 2 time 3: jan 1987 - dec 1990


londt3r3          int      %8.0g                    *   longitude in degrees residence 3 time 3: jan 1987 - dec 1990


londt3r4          byte     %8.0g                    *   longitude in degrees residence 4 time 3: jan 1987 - dec 1990


latmt3r1          byte     %8.0g                    *   latitude in minutes residence 1 time 3: jan 1987 - dec 1990


latmt3r2          byte     %8.0g                    *   latitude in minutes residence 2 time 3: jan 1987 - dec 1990


latmt3r3          byte     %8.0g                    *   latitude in minutes residence 3 time 3: jan 1987 - dec 1990


latmt3r4          byte     %8.0g                    *   latitude in minutes residence 4 time 3: jan 1987 - dec 1990


lonmt3r1          byte     %8.0g                    *   longitude in minutes residence 1 time 3: jan 1987 - dec 1990


lonmt3r2          byte     %8.0g                    *   longitude in minutes residence 2 time 3: jan 1987 - dec 1990


lonmt3r3          byte     %8.0g                    *   longitude in minutes residence 3 time 3: jan 1987 - dec 1990


lonmt3r4          byte     %8.0g                    *   longitude in minutes residence 4 time 3: jan 1987 - dec 1990


mntht3r1          byte     %10.0g                   *   how long did you stay in residence 1 time 3: jan 1987 - dec 1990


mntht3r2          byte     %10.0g                   *   how long did you stay in residence 2 time 3: jan 1987 - dec 1990


mntht3r3          byte     %10.0g                   *   how long did you stay in residence 3 time 3: jan 1987 - dec 1990


mntht3r4          byte     %10.0g                   *   how long did you stay in residence 4 time 3: jan 1987 - dec 1990


oblt3r1           byte     %31.0g        LABG       *   oblast of residence 1 time 3: jan 1987 - dec 1990


oblt3r2           byte     %31.0g        LABG       *   oblast of residence 2 time 3: jan 1987 - dec 1990


oblt3r3           byte     %31.0g        LABG       *   oblast of residence 3 time 3: jan 1987 - dec 1990


oblt3r4           byte     %31.0g        LABG       *   oblast of residence 4 time 3: jan 1987 - dec 1990


latt3r1           byte     %15.0g        LABF       *   latitude direction of residence 1 time 3: jan 1987 - dec 1990


latt3r2           byte     %15.0g        LABF       *   latitude direction of residence 2 time 3: jan 1987 - dec 1990


latt3r3           byte     %15.0g        LABF       *   latitude direction of residence 3 time 3: jan 1987 - dec 1990


latt3r4           byte     %15.0g        LABF       *   latitude direction of residence 4 time 3: jan 1987 - dec 1990


lont3r1           byte     %10.0g        lon        *   longitude direction of residence 1 time 3: jan 1987 - dec 1990


lont3r2           byte     %10.0g        lon        *   longitude direction of residence 2 time 3: jan 1987 - dec 1990


lont3r3           byte     %10.0g        lon        *   longitude direction of residence 3 time 3: jan 1987 - dec 1990


lont3r4           byte     %10.0g        lon        *   longitude direction of residence 4 time 3: jan 1987 - dec 1990


typet3r1          byte     %23.0g        LABL           type of residence 1 time 3: jan 1987 - dec 1990


typet3r2          byte     %23.0g        LABL           type of residence 2 time 3: jan 1987 - dec 1990


typet3r3          byte     %23.0g        LABL           type of residence 3 time 3: jan 1987 - dec 1990


typet3r4          byte     %23.0g        LABL           type of residence 4 time 3: jan 1987 - dec 1990


occt3r1           byte     %22.0g        LABO           occupation while in  residence 1 time 3: jan 1987 - dec 1990


occt3r2           byte     %22.0g        LABO           occupation while in  residence 2 time 3: jan 1987 - dec 1990


occt3r3           byte     %22.0g        LABO           occupation while in  residence 3 time 3: jan 1987 - dec 1990


occt3r4           byte     %22.0g        LABO           occupation while in  residence 4 time 3: jan 1987 - dec 1990


ldrt3r1           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 1 time 3: jan 1987 - dec 1990


ldrt3r2           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 2 time 3: jan 1987 - dec 1990


ldrt3r3           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 3 time 3: jan 1987 - dec 1990


ldrt3r4           byte     %15.0g        LABC       *   did you consume liquid dairy in residence 4 time 3: jan 1987 - dec 1990


sldrt3r1          byte     %20.0g        LABN       *   source of liquid dairy  in residence 1 time 3: jan 1987 - dec 1990


sldrt3r2          byte     %20.0g        LABN       *   source of liquid dairy  in residence 2 time 3: jan 1987 - dec 1990


sldrt3r3          byte     %20.0g        LABN       *   source of liquid dairy  in residence 3 time 3: jan 1987 - dec 1990


sldrt3r4          byte     %20.0g        LABN       *   source of liquid dairy  in residence 4 time 3: jan 1987 - dec 1990


mlldt3r1          int      %8.0g                    *   quantity (in ml) of liquid dairy per week  residence 1 time 3: jan 1987 - dec90


mlldt3r2          int      %8.0g                    *   quantity (in ml) of liquid dairy per week  residence 2 time 3: jan 1987 - dec90


mlldt3r3          int      %8.0g                    *   quantity (in ml) of liquid dairy per week  residence 3 time 3: jan 1987 - dec90


mlldt3r4          int      %8.0g                    *   quantity (in ml) of liquid dairy per week  residence 4 time 3: jan 1987 - dec90


sdrt3r1           byte     %15.0g        LABC       *   did you consume solid dairy in residence 1 time 3: jan 1987 - dec 1990


sdrt3r2           byte     %15.0g        LABC       *   did you consume solid dairy in residence 2 time 3: jan 1987 - dec 1990


sdrt3r3           byte     %15.0g        LABC       *   did you consume solid dairy in residence 3 time 3: jan 1987 - dec 1990


sdrt3r4           byte     %15.0g        LABC       *   did you consume solid dairy in residence 4 time 3: jan 1987 - dec 1990


ssdrt3r1          byte     %20.0g        LABN       *   source of solid dairy in residence 1 time 3: jan 1987 - dec 1990


ssdrt3r2          byte     %20.0g        LABN       *   source of solid dairy in residence 2 time 3: jan 1987 - dec 1990


ssdrt3r3          byte     %20.0g        LABN       *   source of solid dairy in residence 3 time 3: jan 1987 - dec 1990


ssdrt3r4          byte     %20.0g        LABN       *   source of solid dairy in residence 4 time 3: jan 1987 - dec 1990


gldt3r1           int      %8.0g                    *   quantity (in grams) of solid dairy per week res 1 time 3: jan 1987 - dec 1990


gldt3r2           int      %8.0g                    *   quantity (in grams) of solid dairy per week res 2 time 3: jan 1987 - dec 1990


gldt3r3           int      %8.0g                    *   quantity (in grams) of solid dairy per week res 3 time 3: jan 1987 - dec 1990


gldt3r4           byte     %8.0g                    *   quantity (in grams) of solid dairy per week res 4 time 3: jan 1987 - dec 1990


pott3r1           byte     %15.0g        LABC       *   did you consume potatoes in residence 1 time 3: jan 1987 - dec 1990


pott3r2           byte     %15.0g        LABC       *   did you consume potatoes in residence 2 time 3: jan 1987 - dec 1990


pott3r3           byte     %15.0g        LABC       *   did you consume potatoes in residence 3 time 3: jan 1987 - dec 1990


pott3r4           byte     %15.0g        LABC       *   did you consume potatoes in residence 4 time 3: jan 1987 - dec 1990


spott3r1          byte     %20.0g        LABN           source of potatoes in residence 1 time 3: jan 1987 - dec 1990


spott3r2          byte     %20.0g        LABN           source of potatoes in residence 2 time 3: jan 1987 - dec 1990


spott3r3          byte     %20.0g        LABN           source of potatoes in residence 3 time 3: jan 1987 - dec 1990


spott3r4          byte     %20.0g        LABN           source of potatoes in residence 4 time 3: jan 1987 - dec 1990


gpott3r1          int      %8.0g                    *   quantity (in grams) of potatoes per week residence 1 time 3: jan 1987 - dec 1990


gpott3r2          int      %8.0g                    *   quantity (in grams) of potatoes per week residence 2 time 3: jan 1987 - dec 1990


gpott3r3          int      %8.0g                    *   quantity (in grams) of potatoes per week residence 3 time 3: jan 1987 - dec 1990


gpott3r4          int      %8.0g                    *   quantity (in grams) of potatoes per week residence 4 time 3: jan 1987 - dec 1990


prkt3r1           byte     %15.0g        LABC           did you consume pork in residence 1 time 3: jan 1987 - dec 1990


prkt3r2           byte     %15.0g        LABC           did you consume pork in residence 2 time 3: jan 1987 - dec 1990


prkt3r3           byte     %15.0g        LABC           did you consume pork in residence 3 time 3: jan 1987 - dec 1990


prkt3r4           byte     %15.0g        LABC           did you consume pork in residence 4 time 3: jan 1987 - dec 1990


sprkt3r1          byte     %20.0g        LABN           source of pork in residence 1 time 3: jan 1987 - dec 1990


sprkt3r2          byte     %20.0g        LABN           source of pork in residence 2 time 3: jan 1987 - dec 1990


sprkt3r3          byte     %20.0g        LABN           source of pork in residence 3 time 3: jan 1987 - dec 1990


sprkt3r4          byte     %20.0g        LABN           source of pork in residence 4 time 3: jan 1987 - dec 1990


gprkt3r1          long     %8.0g                    *   quantity (in grams) of pork per week residence 1 time 3: jan 1987 - dec 1990


gprkt3r2          long     %8.0g                    *   quantity (in grams) of pork per week residence 2 time 3: jan 1987 - dec 1990


gprkt3r3          long     %8.0g                    *   quantity (in grams) of pork per week residence 3 time 3: jan 1987 - dec 1990


gprkt3r4          int      %8.0g                    *   quantity (in grams) of pork per week residence 4 time 3: jan 1987 - dec 1990


beft3r1           byte     %15.0g        LABC           did you consume beef in residence 1 time 3: jan 1987 - dec 1990


beft3r2           byte     %15.0g        LABC           did you consume beef in residence 2 time 3: jan 1987 - dec 1990


beft3r3           byte     %15.0g        LABC           did you consume beef in residence 3 time 3: jan 1987 - dec 1990


beft3r4           byte     %15.0g        LABC           did you consume beef in residence 4 time 3: jan 1987 - dec 1990


sbeft3r1          byte     %20.0g        LABN           source of beef in residence 1 time 3: jan 1987 - dec 1990


sbeft3r2          byte     %20.0g        LABN           source of beef in residence 2 time 3: jan 1987 - dec 1990


sbeft3r3          byte     %20.0g        LABN           source of beef in residence 3 time 3: jan 1987 - dec 1990


sbeft3r4          byte     %20.0g        LABN           source of beef in residence 4 time 3: jan 1987 - dec 1990


gbeft3r1          long     %8.0g                    *   quantity (in grams) of beef per week residence 1 time 3: jan 1987 - dec 1990


gbeft3r2          int      %8.0g                    *   quantity (in grams) of beef per week residence 2 time 3: jan 1987 - dec 1990


gbeft3r3          int      %8.0g                    *   quantity (in grams) of beef per week residence 3 time 3: jan 1987 - dec 1990


gbeft3r4          int      %8.0g                    *   quantity (in grams) of beef per week residence 4 time 3: jan 1987 - dec 1990


pltt3r1           byte     %15.0g        LABC           did you consume poultry in residence 1 time 3: jan 1987 - dec 1990


pltt3r2           byte     %15.0g        LABC           did you consume poultry in residence 2 time 3: jan 1987 - dec 1990


pltt3r3           byte     %15.0g        LABC           did you consume poultry in residence 3 time 3: jan 1987 - dec 1990


pltt3r4           byte     %15.0g        LABC           did you consume poultry in residence 4 time 3: jan 1987 - dec 1990


spltt3r1          byte     %20.0g        LABN           source of paultry  in residence 1 time 3: jan 1987 - dec 1990


spltt3r2          byte     %20.0g        LABN           source of paultry  in residence 2 time 3: jan 1987 - dec 1990


spltt3r3          byte     %20.0g        LABN           source of paultry  in residence 3 time 3: jan 1987 - dec 1990


spltt3r4          byte     %20.0g        LABN           source of paultry  in residence 4 time 3: jan 1987 - dec 1990


gpltt3r1          long     %8.0g                    *   quantity (in grams) of paultry per week residence 1 time 3: jan 1987 - dec 1990


gpltt3r2          int      %8.0g                    *   quantity (in grams) of paultry per week residence 2 time 3: jan 1987 - dec 1990


gpltt3r3          int      %8.0g                    *   quantity (in grams) of paultry per week residence 3 time 3: jan 1987 - dec 1990


gpltt3r4          int      %8.0g                    *   quantity (in grams) of paultry per week residence 4 time 3: jan 1987 - dec 1990


msht3r1           byte     %15.0g        LABC           did you consume mushrooms  in residence 1 time 3: jan 1987 - dec 1990


msht3r2           byte     %15.0g        LABC           did you consume mushrooms  in residence 2 time 3: jan 1987 - dec 1990


msht3r3           byte     %15.0g        LABC           did you consume mushrooms  in residence 3 time 3: jan 1987 - dec 1990


msht3r4           byte     %15.0g        LABC           did you consume mushrooms  in residence 4 time 3: jan 1987 - dec 1990


smsht3r1          byte     %20.0g        LABN           source of mushrooms  in residence 1 time 3: jan 1987 - dec 1990


smsht3r2          byte     %20.0g        LABN           source of mushrooms  in residence 2 time 3: jan 1987 - dec 1990


smsht3r3          byte     %20.0g        LABN           source of mushrooms  in residence 3 time 3: jan 1987 - dec 1990


smsht3r4          byte     %20.0g        LABN           source of mushrooms  in residence 4 time 3: jan 1987 - dec 1990


gmsht3r1          int      %8.0g                    *   quantity (in grams) of mushroom per week residence 1 time 3: jan 1987 - dec 1990


gmsht3r2          int      %8.0g                    *   quantity (in grams) of mushroom per week residence 2 time 3: jan 1987 - dec 1990


gmsht3r3          int      %8.0g                    *   quantity (in grams) of mushroom per week residence 3 time 3: jan 1987 - dec 1990


gmsht3r4          byte     %8.0g                    *   quantity (in grams) of mushroom per week residence 4 time 3: jan 1987 - dec 1990


sett4r1           str23    %23s                     *   town of residence 1 time 4: jan 1991-now


sett4r2           str32    %32s                         town of residence 2 time 4: jan 1991-now


sett4r3           str32    %32s                         town of residence 3 time 4: jan 1991-now


sett4r4           str32    %32s                         town of residence 4 time 4: jan 1991-now


rait4r1           str23    %23s                         raion of residence 1 time 4: jan 1991-now


rait4r2           str32    %32s                         raion of residence 2 time 4: jan1991-now


rait4r3           str32    %32s                         raion of residence 3 time 4: jan1991-now


rait4r4           str32    %32s                         raion of residence 4 time 4: jan 1991-now


latdt4r1          byte     %8.0g                    *   latitude in degrees residence 1 time 4: jan 1991-now


latdt4r2          byte     %8.0g                    *   latitude in degrees residence 2 time 4: jan 1991-now


latdt4r3          byte     %8.0g                    *   latitude in degrees residence 3 time 4: jan 1991-now


latdt4r4          byte     %8.0g                    *   latitude in degrees residence 4 time 4: jan 1991-now


londt4r1          int      %8.0g                    *   longitude in degrees  residence 1 time 4: jan 1991-now


londt4r2          int      %8.0g                    *   longitude in degrees  residence 2 time 4: jan 1991-now


londt4r3          byte     %8.0g                    *   longitude in degrees  residence 3 time 4: jan 1991-now


londt4r4          byte     %8.0g                    *   longitude in degrees  residence 4 time 4: jan 1991-now


latmt4r1          byte     %8.0g                    *   latitude in minutes residence 1 time 4: jan 1991-now


latmt4r2          byte     %8.0g                    *   latitude in minutes residence 2 time 4: jan 1991-now


latmt4r3          byte     %8.0g                    *   latitude in minutes residence 3 time 4: jan 1991-now


latmt4r4          byte     %8.0g                    *   latitude in minutes residence 4 time 4: jan 1991-now


lonmt4r1          byte     %8.0g                    *   longitude in minutes  residence 1 time 4: jan 1991-now


lonmt4r2          byte     %8.0g                    *   longitude in minutes  residence 2 time 4: jan 1991-now


lonmt4r3          byte     %8.0g                    *   longitude in minutes  residence 3 time 4: jan 1991-now


lonmt4r4          byte     %8.0g                    *   longitude in minutes  residence 4 time 4: jan 1991-now


mntht4r1          int      %8.0g                    *   how long did you stay in residence 1 time 4: jan 1991-now


mntht4r2          int      %8.0g                    *   how long did you stay in residence 2 time 4: jan 1991-now


mntht4r3          int      %8.0g                    *   how long did you stay in residence 3 time 4: jan 1991-now


mntht4r4          byte     %8.0g                    *   how long did you stay in residence 4 time 4: jan 1991-now


oblt4r1           byte     %31.0g        LABG           oblast of the residence 1 time 4: jan 1991-now


oblt4r2           byte     %31.0g        LABG           oblast of the residence 2 time 4: jan 1991-now


oblt4r3           byte     %31.0g        LABG           oblast of the residence 3 time 4: jan 1991-now


oblt4r4           byte     %31.0g        LABG           oblast of the residence 4 time 4: jan 1991-now


latt4r1           byte     %15.0g        LABF           direction of latitude of  residence 1 time 4: jan 1991-now


latt4r2           byte     %15.0g        LABF           direction of latitude of residence 2 time 4: jan 1991-now


latt4r3           byte     %15.0g        LABF           direction of latitude of residence 3 time 4: jan 1991-now


latt4r4           byte     %15.0g        LABF           direction of latitude of residence 4 time 4: jan 1991-now


lont4r1           byte     %10.0g        lon            direction of longitude of residence 1 time 4: jan 1991-now


lont4r2           byte     %10.0g        lon            direction of longitude of residence 2 time 4: jan 1991-now


lont4r3           byte     %10.0g        lon            direction of longitude of residence 3 time 4: jan 1991-now


lont4r4           byte     %10.0g        lon            direction of longitude of residence 4 time 4: jan 1991-now


typet4r1          byte     %23.0g        LABL           type of  residence 1 time 4: jan 1991-now


typet4r2          byte     %23.0g        LABL           type of  residence 2 time 4: jan 1991-now


typet4r3          byte     %23.0g        LABL           type of  residence 3 time 4: jan 1991-now


typet4r4          byte     %23.0g        LABL           type of  residence 4 time 4: jan 1991-now


occt4r1           byte     %22.0g        LABM           ocupation when in residence 1 time 4: jan 1991-now


occt4r2           byte     %22.0g        LABM           ocupation when in residence 2 time 4: jan 1991-now


occt4r3           byte     %22.0g        LABM           ocupation when in residence 3 time 4: jan 1991-now


occt4r4           byte     %22.0g        LABM           ocupation when in residence 4 time 4: jan 1991-now


ldrt4r1           byte     %15.0g        LABC           did you consume liquid dairy products in residence 1 time 4: jan 1991-now


ldrt4r2           byte     %15.0g        LABC           did you consume liquid dairy products in residence 2 time 4: jan 1991-now


ldrt4r3           byte     %15.0g        LABC           did you consume liquid dairy products in residence 3 time 4: jan 1991-now


ldrt4r4           byte     %15.0g        LABC           did you consume liquid dairy products in residence 4 time 4: jan 1991-now


sldrt4r1          byte     %20.0g        LABN       *   source of liquid dairy products in residence 1 time 4: jan 1991-now


sldrt4r2          byte     %20.0g        LABN       *   source of liquid dairy products in residence 2 time 4: jan 1991-now


sldrt4r3          byte     %20.0g        LABN       *   source of liquid dairy products in residence 3 time 4: jan 1991-now


sldrt4r4          byte     %20.0g        LABN       *   source of liquid dairy products in residence 4 time 4: jan 1991-now


mlldt4r1          int      %8.0g                    *   quantity (in ml) of liquid dairy products in residence 1 time 4: jan 1991-now


mlldt4r2          int      %8.0g                    *   quantity (in ml) of liquid dairy products in residence 2 time 4: jan 1991-now


mlldt4r3          int      %8.0g                    *   quantity (in ml) of liquid dairy products in residence 3 time 4: jan 1991-now


mlldt4r4          int      %8.0g                    *   quantity (in ml) of liquid dairy products in residence 4 time 4: jan 1991-now


sdrt4r1           byte     %15.0g        LABC       *   did you consume solid dairy products in residence 1 time 4: jan 1991-now


sdrt4r2           byte     %15.0g        LABC       *   did you consume solid dairy products in residence 2 time 4: jan 1991-now


sdrt4r3           byte     %15.0g        LABC       *   did you consume solid dairy products in residence 3 time 4: jan 1991-now


sdrt4r4           byte     %15.0g        LABC       *   did you consume solid dairy products in residence 4 time 4: jan 1991-now


ssdrt4r1          byte     %20.0g        LABN       *   source of solid dairy products in residence 1 time 4: jan 1991-now


ssdrt4r2          byte     %20.0g        LABN       *   source of solid dairy products in residence 2 time 4: jan 1991-now


ssdrt4r3          byte     %20.0g        LABN       *   source of solid dairy products in residence 3 time 4: jan 1991-now


ssdrt4r4          byte     %20.0g        LABN       *   source of solid dairy products in residence 4 time 4: jan 1991-now


gldt4r1           long     %8.0g                    *   quantity (in grams) of solid dairy in residence 1 time 4: jan 1991-now


gldt4r2           long     %8.0g                    *   quantity (in grams) of solid dairy in residence 2 time 4: jan 1991-now


gldt4r3           long     %8.0g                    *   quantity (in grams) of solid dairy in residence 3 time 4: jan 1991-now


gldt4r4           int      %8.0g                    *   quantity (in grams) of solid dairy in residence 4 time 4: jan 1991-now


pott4r1           byte     %15.0g        LABC           did you consume potatoes in residence 1 time 4: jan 1991-now


pott4r2           byte     %15.0g        LABC           did you consume potatoes in residence 2 time 4: jan 1991-now


pott4r3           byte     %15.0g        LABC           did you consume potatoes in residence 3 time 4: jan 1991-now


pott4r4           byte     %15.0g        LABC           did you consume potatoes in residence 4 time 4: jan 1991-now


spott4r1          byte     %20.0g        LABN       *   source of potatoes in residence 1 time 4: jan 1991-now


spott4r2          byte     %20.0g        LABN       *   source of potatoes in residence 2 time 4: jan 1991-now


spott4r3          byte     %20.0g        LABN       *   source of potatoes in residence 3 time 4: jan 1991-now


spott4r4          byte     %20.0g        LABN       *   source of potatoes in residence 4 time 4: jan 1991-now


gpott4r1          long     %8.0g                    *   quantity of potatoes (in grams)  per week in residence 1 time 4: jan 1991-now


gpott4r2          long     %8.0g                    *   quantity of potatoes (in grams)  per week in residence 2 time 4: jan 1991-now


gpott4r3          int      %8.0g                    *   quantity of potatoes (in grams)  per week in residence 3 time 4: jan 1991-now


gpott4r4          int      %8.0g                    *   quantity of potatoes (in grams)  per week in residence 4 time 4: jan 1991-now


prkt4r1           byte     %15.0g        LABC           did you consume pork in residence 1 time 4: jan 1991-now


prkt4r2           byte     %15.0g        LABC           did you consume pork in residence 2 time 4: jan 1991-now


prkt4r3           byte     %15.0g        LABC           did you consume pork in residence 3 time 4: jan 1991-now


prkt4r4           byte     %15.0g        LABC           did you consume pork in residence 4 time 4: jan 1991-now


sprkt4r1          byte     %20.0g        LABN       *   source of pork  in residence 1 time 4: jan 1991-now


sprkt4r2          byte     %20.0g        LABN       *   source of pork  in residence 2 time 4: jan 1991-now


sprkt4r3          byte     %20.0g        LABN       *   source of pork  in residence 3 time 4: jan 1991-now


sprkt4r4          byte     %20.0g        LABN       *   source of pork  in residence 4 time 4: jan 1991-now


gprkt4r1          int      %8.0g                    *   quantity of pork (in grams) per week in residence 1 time 4: jan 1991-now


gprkt4r2          int      %8.0g                    *   quantity of pork (in grams) per week in residence 2 time 4: jan 1991-now


gprkt4r3          int      %8.0g                    *   quantity of pork (in grams) per week in residence 3 time 4: jan 1991-now


gprkt4r4          int      %8.0g                    *   quantity of pork (in grams) per week in residence 4 time 4: jan 1991-now


beft4r1           byte     %15.0g        LABC           did you consume beef in residence 1 time 4: jan 1991-now


beft4r2           byte     %15.0g        LABC           did you consume beef in residence 2 time 4: jan 1991-now


beft4r3           byte     %15.0g        LABC           did you consume beef in residence 3 time 4: jan 1991-now


beft4r4           byte     %15.0g        LABC           did you consume beef in residence 4 time 4: jan 1991-now


sbeft4r1          byte     %20.0g        LABN           source of beef in residence 1 in time 4: jan 1991-now


sbeft4r2          byte     %20.0g        LABN           source of beef in residence 2 in time 4: jan 1991-now


sbeft4r3          byte     %20.0g        LABN           source of beef in residence 3 in time 4: jan 1991-now


sbeft4r4          byte     %20.0g        LABN           source of beef in residence 4 in time 4: jan 1991-now


gbeft4r1          long     %8.0g                    *   quantity of beef (in grams) per week in residence 1 in time 4: jan 1991-now


gbeft4r2          int      %8.0g                    *   quantity of beef (in grams) per week in residence 2 in time 4: jan 1991-now


gbeft4r3          int      %8.0g                    *   quantity of beef (in grams) per week in residence 3 in time 4: jan 1991-now


gbeft4r4          int      %8.0g                    *   quantity of beef (in grams) per week in residence 4 in time 4: jan 1991-now


pltt4r1           byte     %15.0g        LABC       *   did you consume poultry  in residence 1 in time 4: jan 1991-now


pltt4r2           byte     %15.0g        LABC       *   did you consume poultry  in residence 2 in time 4: jan 1991-now


pltt4r3           byte     %15.0g        LABC       *   did you consume poultry  in residence 3 in time 4: jan 1991-now


pltt4r4           byte     %15.0g        LABC       *   did you consume poultry  in residence 4 in time 4: jan 1991-now


spltt4r1          byte     %20.0g        LABN           source of paultry  in residence 1 in time 4: jan 1991-now


spltt4r2          byte     %20.0g        LABN           source of paultry  in residence 2 in time 4: jan 1991-now


spltt4r3          byte     %20.0g        LABN           source of paultry  in residence 3 in time 4: jan 1991-now


spltt4r4          byte     %20.0g        LABN           source of paultry  in residence 4 in time 4: jan 1991-now


gpltt4r1          long     %8.0g                    *   quantity of paultry (in grams) per week  in residence 1 in time 4: jan 1991-now


gpltt4r2          int      %8.0g                    *   quantity of paultry (in grams) per week  in residence 2 in time 4: jan 1991-now


gpltt4r3          int      %8.0g                    *   quantity of paultry (in grams) per week  in residence 3 in time 4: jan 1991-now


gpltt4r4          int      %8.0g                    *   quantity of paultry (in grams) per week  in residence 4 in time 4: jan 1991-now


msht4r1           byte     %15.0g        LABC       *   did you consume mushrooms  in residence 1 in time 4: jan 1991-now


msht4r2           byte     %15.0g        LABC       *   did you consume mushrooms  in residence 2 in time 4: jan 1991-now


msht4r3           byte     %15.0g        LABC       *   did you consume mushrooms  in residence 3 in time 4: jan 1991-now


msht4r4           byte     %15.0g        LABC       *   did you consume mushrooms  in residence 4 in time 4: jan 1991-now


smsht4r1          byte     %20.0g        LABN           source of mushrooms  in residence 1 in time 4: jan 1991-now


smsht4r2          byte     %20.0g        LABN           source of mushrooms  in residence 2 in time 4: jan 1991-now


smsht4r3          byte     %20.0g        LABN           source of mushrooms  in residence 2 in time 4: jan 1991-now


smsht4r4          byte     %20.0g        LABN           source of mushrooms  in residence 3 in time 4: jan 1991-now


gmsht4r1          int      %8.0g                    *   quantity of mushroom (in grams) per week  in residence 1 in time 4: jan 1991-now


gmsht4r2          int      %8.0g                    *   quantity of mushroom (in grams) per week  in residence 2 in time 4: jan 1991-now


gmsht4r3          int      %8.0g                    *   quantity of mushroom (in grams) per week  in residence 3 in time 4: jan 1991-now


gmsht4r4          byte     %8.0g                    *   quantity of mushroom (in grams) per week  in residence 4 in time 4: jan 1991-now


csflfrnd          byte     %15.0g        LABB       *   let your feelings out to a friend?


csrearr           byte     %15.0g        LABB       *   rearranged things around you so that your problem had the best chance of being s


csbrstrm          byte     %15.0g        LABB           brainstormed all possible solutions before deciding what to do?


csdist            byte     %15.0g        LABB           tried to distract yourself from the problem?


csaccsy           byte     %15.0g        LABB           accepted sympathy and understanding from someone?


cskpothe          byte     %15.0g        LABB           did all you could to keep others from seeing how bad things really were?


cstkpeop          byte     %15.0g        LABB       *   talked to people about the situation because talking about it helped you to feel


cssetgoa          byte     %15.0g        LABB           set some goals for yourself to deal with the situation?


cswghopt          byte     %15.0g        LABB           weighed your options very carefully?


csddream          byte     %15.0g        LABB           daydreamed about a better time?


csdifsov          byte     %15.0g        LABB           tried different ways to solve the problem until you found one that worked?


cscofear          byte     %15.0g        LABB           confided your fears and worries to a friend or a relative?


csalone           byte     %15.0g        LABB           spent more time than usual alone?


cstldpep          byte     %15.0g        LABB       *   told people about the situation because just talking about it helped you to come


csstngs           byte     %15.0g        LABB           thought about what needed to be done to straighten things out?


csflatt           byte     %15.0g        LABB           turned your full attention to solving the problem?


csactpl           byte     %15.0g        LABB           formed a plan of action in your mind?


cstv              byte     %15.0g        LABB           watched television more than usual?


csfrndpr          byte     %15.0g        LABB           went to someone (friend or professional) in order to help you feel better?


csstndfr          byte     %15.0g        LABB           stood firm and fought for what you wanted in the situation?


csavdppl          byte     %15.0g        LABB           avoided being with people in general?


cshbspor          byte     %15.0g        LABB           buried yourself in a hobby or sports activity to avoid the problem?


csfriend          byte     %15.0g        LABB           went to a friend to help you feel better about the problem?


csadvice          byte     %15.0g        LABB           went to a friend for advice on how to change the situation?


csacsymp          byte     %15.0g        LABB           accepted sympathy and understanding from friends who had the same problem?


cssleep           byte     %15.0g        LABB           slept more than usual?


csfantsy          byte     %15.0g        LABB           fantasized about how things could have been different?


csidnovl          byte     %15.0g        LABB           identified with characters in novels or movies?


cssolvpr          byte     %15.0g        LABB           tried to solve the problem?


cslvbe            byte     %15.0g        LABB           wished that people would just leave you alone?


csachelp          byte     %15.0g        LABB           accepted help from a friend or relative?


csreasur          byte     %15.0g        LABB           sought reassurance from those who know you best?


csplnact          byte     %15.0g        LABB           tried to carefully plan a course of action rather than acting on impulse?


psolv             byte     %8.0g                        subscale i = "problem solving"


socsup            byte     %8.0g                        subscale ii = "seeking social support"


avoid             byte     %8.0g                        subscale iii = "avoidance"


hptired           byte     %12.0g        HPLabel        i’m tired all the time


hppainit          byte     %12.0g        HPLabel        i have pain at night


hpgtdwn           byte     %12.0g        HPLabel        things are getting me down


hpunpain          byte     %12.0g        HPLabel        i have unbearable pain


hpslepil          byte     %12.0g        HPLabel        i take pills to help me sleep


hpnojoy           byte     %12.0g        HPLabel        i’ve forgotten what it’s like to enjoy myself


hponedge          byte     %12.0g        HPLabel        i’m feeling on edge


hpcngpos          byte     %12.0g        HPLabel        i find it painful to change position


hplonely          byte     %12.0g        HPLabel        i feel lonely


hpwlkinr          byte     %12.0g        HPLabel        i can walk about only indoors


hpnobend          byte     %12.0g        HPLabel        i find it hard to bend


hpalefrt          byte     %12.0g        HPLabel        everything is an effort


hpwkgrly          byte     %12.0g        HPLabel        i’m waking up in the early hours of the morning


hpnowlk           byte     %12.0g        HPLabel        i’m unable to walk at all


hphrdcnt          byte     %12.0g        HPLabel        i’m finding it hard to make contact with people


hpdaydrg          byte     %12.0g        HPLabel        the days seem to drag


hpstairs          byte     %12.0g        HPLabel        i have trouble getting up and down stairs and steps


hphrdrch          byte     %12.0g        HPLabel        i find it hard to reach for things


hpwlkpai          byte     %12.0g        HPLabel        i’m in pain when i walk


hptemper          byte     %12.0g        HPLabel        i lose my temper easily these days


hpnoclse          byte     %12.0g        HPLabel        i feel like there is nobody that i am close to


hpawake           byte     %12.0g        HPLabel        i lie awake for most of the night


hplocntr          byte     %12.0g        HPLabel        i feel as if i’m losing control


hpstdpai          byte     %12.0g        HPLabel        i’m in pain when i’m standing


hphardre          byte     %12.0g        HPLabel        i find it hard to get dressed by myself


hpnoergy          byte     %12.0g        HPLabel        i soon run out of energy


hphrdstd          byte     %12.0g        HPLabel        i find it hard to stand for long (e.g. at the kitchen sink, waiting in line)


hpconpai          byte     %12.0g        HPLabel        i’m in constant pain.


hplgslee          byte     %12.0g        HPLabel        it takes me a long time to get to sleep.


hpburden          byte     %12.0g        HPLabel        i feel i am a burden to people.


hpwryawk          byte     %12.0g        HPLabel        worry is keeping me awake at night.


hpnolive          byte     %12.0g        HPLabel        i feel that life is not worth living.


hpbadslp          byte     %12.0g        HPLabel        i sleep badly at night.


hpgtalng          byte     %12.0g        HPLabel        i’m finding it hard to get along with people.


hphlpwlk          byte     %12.0g        HPLabel        i need help to walk about outside (e.g. a walking aid or someone to support me).


hpstrspn          byte     %12.0g        HPLabel        i’m in pain when going up or down stairs.


hpamdprs          byte     %12.0g        HPLabel        i wake up feeling depressed


hpsitpai          byte     %12.0g        HPLabel        i’m in pain when i’m sitting.


enlev             double   %9.0g                        energy level (el)


pain              double   %9.0g                        pain (p)


emreac            double   %9.0g                        emotional reaction (er)


sleep             double   %9.0g                        sleep (s)


socisol           double   %9.0g                        social isolation (si)


phabil            double   %9.0g                        physical abilities (pa)


hpprbwk           byte     %12.0g        HPLabel        health causes problems at work


hpprbcln          byte     %12.0g        HPLabel    *   health causes problems taking care of home


hpprobsc          byte     %12.0g        HPLabel        health causing problems with social life


hpprobho          byte     %12.0g        HPLabel        health causing problems with home life


hpprosex          byte     %12.0g        HPLabel        health cauing problems with sex life


hpproint          byte     %12.0g        HPLabel        health causing problems with interests and hobbies


hpprovac          byte     %12.0g        HPLabel        health causing problems with vacations


hthprof           byte     %8.0g                        health profile subscale


ffriend           byte     %18.0g        LABD       *   before the chornobyl event in 1986 i had more close friends than i have now.


fchorn            byte     %18.0g        LABD       *   if something happens that reminds me of chornobyl. i become very distressed and


fguilt            byte     %18.0g        LABD           i feel guilty over things i did around the time of chornobyl


fpush             byte     %18.0g        LABD       *   since the event i find that if someone pushes me too far, i am likely to become


fnight            byte     %18.0g        LABD           i have nightmares about chornobyl.


fdead             byte     %18.0g        LABD       *   when i think of some of the things i did at the time of chornobyl i wish i were


fnofeel           byte     %18.0g        LABD           since chornobyl, it seems as if i have no feelings.


flived            byte     %18.0g        LABD           i wonder why i lived when others died.


fsituat           byte     %18.0g        LABD           being in certain situations makes me feel as though i am back in the event.


flaugh            byte     %18.0g        LABD       *   since chornobyl it seems that i do not laugh or cry about the same things that


fnoise            byte     %18.0g        LABD           since chornobyl unexpected noises make me jump.


falcoh            byte     %18.0g        LABD       *   i have used alcohol or other drugs to help me sleep or to make me forget the eve


fafraid           byte     %18.0g        LABD           since chornobyl  i have been afraid to sleep at night


fstayaw           byte     %18.0g        LABD       *   i try to stay away from anything that will remind me of things which happened du


fremem            byte     %18.0g        LABD           i have difficulty remembering some things which happened during the event.


fanxio            byte     %18.0g        LABD           if something happens that reminds me of chornobyl, i get anxious and panicky.


fremind           byte     %18.0g        LABD           things i see or hear often remind me of the chornobyl event.


fdontth           byte     %18.0g        LABD           i often think about the event even when i don’t mean to.


femot             byte     %18.0g        LABD           i am able to get emotionally close to others.


fkill             byte     %18.0g        LABD           lately i have felt like killing myself.


fasleep           byte     %18.0g        LABD           i fall asleep stay asleep and awaken only when the alarm goes off.


fdream            byte     %18.0g        LABD       *   my dreams are so real that i awaken in a cold sweat and force myself to stay awa


fgoon             byte     %18.0g        LABD           i feel like i cannot go on.


fenjoy            byte     %18.0g        LABD           i still enjoy doing many things that i used to enjoy.


fconcen           byte     %18.0g        LABD           i have trouble concentrating on tasks.


fcomp             byte     %18.0g        LABD           i enjoy the company of others.


ffallas           byte     %18.0g        LABD           i fall asleep easily at night.


funder            byte     %18.0g        LABD           no one understands how i feel, not even my family.


fcool             byte     %18.0g        LABD           lately, i lose my cool and explode of minor everyday things.


falert            byte     %18.0g        LABD           i feel alert and on guard much of the time.


instsym           byte     %8.0g                        intrusion symptom score


avoisym           byte     %8.0g                        avoidance symptom score


aroussym          byte     %8.0g                        arousal symptom score


suicsym           byte     %8.0g                        suicidal/guilt score


bsnerv            byte     %20.0g        LABE           nervousness or shakiness inside


bsfaint           byte     %20.0g        LABE           faintness or dizziness


bsidea            byte     %20.0g        LABE           the idea that someone else can control your thoughts


bsothers          byte     %20.0g        LABE           feeling others are to blame for most of your troubles


bsnomem           byte     %20.0g        LABE           trouble remembering things


bsannoy           byte     %20.0g        LABE           feeling easily annoyed or irritated


bspain            byte     %20.0g        LABE           pains in the heart or chest


bsafraid          byte     %20.0g        LABE           feeling afraid in open spaces


bsendlif          byte     %20.0g        LABE           thoughts of ending your life


bstrust           byte     %20.0g        LABE           feeling that most people cannot be trusted


bseat             byte     %20.0g        LABE           poor appetite


bsscared          byte     %20.0g        LABE           suddenly scared for no reason


bstemper          byte     %20.0g        LABE           temper outbursts that you could not control


bslonely          byte     %20.0g        LABE           feeling lonely even when you are with people


bsblock           byte     %20.0g        LABE           feeling blocked in getting things done


bsalone           byte     %20.0g        LABE           feeling lonely


bsblue            byte     %20.0g        LABE           feeling blue


bsnoint           byte     %20.0g        LABE           feeling no interest in things


bsfear            byte     %20.0g        LABE           feeling fearful


bshurt            byte     %20.0g        LABE           your feelings being easily hurt


bsnofrd           byte     %20.0g        LABE           feeling that people are unfriendly or dislike you


bsinf             byte     %20.0g        LABE           feeling inferior to others


bsnausea          byte     %20.0g        LABE           nausea or upset stomach


bswatch           byte     %20.0g        LABE           feeling that you are watched or talked about by others


bsnoslp           byte     %20.0g        LABE           trouble falling asleep


bscheck           byte     %20.0g        LABE           having to check and double-check what you do


bsnodec           byte     %20.0g        LABE           difficulty making decisions


bsnotrav          byte     %20.0g        LABE           feeling afraid to travel on buses,undergrounds or trains


bsnobrth          byte     %20.0g        LABE           trouble getting your breath


bshtcold          byte     %20.0g        LABE           hot or cold spells


bsavoid           byte     %20.0g        LABE           having to avoid certain things, places, or activities because they frighten you


bsblank           byte     %20.0g        LABE           your mind going blank


bsnumb            byte     %20.0g        LABE           numbness or tingling in parts of your body


bspunish          byte     %20.0g        LABE           the idea that you should be punished for your sins


bshoples          byte     %20.0g        LABE           feeling hopeless about the future


bsnothk           byte     %20.0g        LABE           trouble concentrating


bsweak            byte     %20.0g        LABE           feeling weak in parts of your body


bstense           byte     %20.0g        LABE           feeling tense or keyed up


bsdeath           byte     %20.0g        LABE           thoughts of death or dying


bsbeat            byte     %20.0g        LABE           having urges to beat, injure or harm someone


bsbreak           byte     %20.0g        LABE           having urges to break or smash things


bsconsc           byte     %20.0g        LABE           feeling very self-conscious with others


bsuneasy          byte     %20.0g        LABE           feeling uneasy in crowds


bsnoclse          byte     %20.0g        LABE           never feeling close to another person


bspanic           byte     %20.0g        LABE           spells of terror or panic


bsargue           byte     %20.0g        LABE           getting into frequent arguments


bsnerv_a          byte     %20.0g        LABE           feeling nervous when you are left alone


bscredit          byte     %20.0g        LABE           others not giving you proper credit for your achievements


bsnosit           byte     %20.0g        LABE           feeling so restless you couldn’t sit still


bsworth           byte     %20.0g        LABE           feelings of worthlessness


bsadvan           byte     %20.0g        LABE           feeling that people will take advantage of you if you let them


bsguilt           byte     %20.0g        LABE           feeling of guilt


bswrong           byte     %20.0g        LABE           the idea that something is wrong with your mind


possym            int      %8.0g                        positive symptom total


somatiz           byte     %8.0g                        somatization


obsess            byte     %8.0g                        obsession-compulsion


interper          byte     %8.0g                        interpersonal sensitivity


depress           byte     %8.0g                        depression


anxiety           byte     %8.0g                        anxiety


hostilit          byte     %8.0g                        hostility


phobanx           byte     %8.0g                        phobic anxiety


paran             byte     %8.0g                        paranoid ideation


psychot           byte     %8.0g                        psychoticism


globseve          double   %9.0g                        global severity


CSprbslv          byte     %9.0g                        Coping Problem Solving Subscale


CSsocspt          byte     %9.0g                        Coping social support subscale


CSavoid           byte     %9.0g                        Coping Avoidance subscale


WHP1el            double   %9.0g


WHP2p             double   %9.0g


WHP3er            double   %9.0g


WHP4p             double   %9.0g


WHP5s             double   %9.0g


WHP6er            double   %9.0g


WHP7er            double   %9.0g


WHP8p             double   %9.0g


WHP9si            double   %9.0g


WHP10pa           double   %9.0g


WHP11pa           double   %9.0g


WHP12el           double   %9.0g


WHP13s            double   %9.0g


WHP14pa           double   %9.0g


WHP15si           double   %9.0g


WHP16er           double   %9.0g


WHP17pa           double   %9.0g


WHP18pa           double   %9.0g


WHP19p            double   %9.0g


WHP20er           double   %9.0g


WHP21si           double   %9.0g


WHP22s            double   %9.0g


WHP23er           double   %9.0g


WHP24p            double   %9.0g


WHP25pa           double   %9.0g


WHP26el           byte     %9.0g


WHP27pa           double   %9.0g


WHP28ps           double   %9.0g


WHP29s            double   %9.0g


WHP30si           double   %9.0g


WHP31er           double   %9.0g


WHP32er           double   %9.0g


WHP33s            double   %9.0g


WHP34si           double   %9.0g


WHP35pa           double   %9.0g


WHP36p            double   %9.0g


WHP37er           double   %9.0g


WHP38p            double   %9.0g


whp23er           double   %9.0g


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


WHPpain           double   %9.0g                        Wtd Health Profile Pain Pt 1 subscale


WHPer             double   %9.0g                        Wtd Health Profile Emotional reaction Pt 1 subscale


WHPsleep          double   %9.0g                        Wtd Health Profile Sleep Pt 1 subscale


WHPsociso         double   %9.0g                        Wtd Health Profile Social Isolation Pt 1 subscale


WHPpa             double   %9.0g                        Wtd Health Profile Physical Ability Pt 1 Subscale


HP2work           byte     %9.0g         hp2fmt         Nottingham Health profile subscale Part2: paid employment


HP2hmcare         byte     %9.0g         hp2fmt         Hlth profile Pt2: Home cleaning, cooking and repairs


HP2probsoc        byte     %9.0g         hp2fmt         Hlth profile Pt2: Hlth causing probs with social life


HP2pbfhm          byte     %9.0g         hp2fmt         Hlth profile Pt2: Hlth causing probs with family members at home


HP2sxlife         byte     %9.0g         hp2fmt         Hlth profile Pt2: Hlth causing probs with sex life


HP2inthob         byte     %9.0g         hp2fmt         Hlth profile Pt2: Hlth probs interfering with interests & hobbies


HP2vacatn         byte     %9.0g         hp2fmt         Hlth profile Pt2: Hlth probs interfering with vacations


BSItotal          int      %9.0g                        Basic symptom inventory total scale score


lBSItotal         double   %9.0g                        Ln(bsItotal)


BSIposymp         int      %9.0g                        Brief Symptom inventory positive symptom total subscale


BSIglobsi         double   %9.0g                        Brief Symptom Inventory Global Severity (mean) Index


BSIsoma           byte     %9.0g                        Basic symptom inventory obsessive compulsive subscale


BSIoc             byte     %9.0g                        Basic Symptom Inventory Obsessive compulsive subscale


BSIips            byte     %9.0g                        Basic symptom invenstory interpersonal sensitivity subscale


BSIdep            byte     %9.0g                        Basic symptom inventory Depression subscale


BSIanx            byte     %9.0g                        Basic symptom inventory Anxiety subscale


BSIphanx          byte     %9.0g                        Basic symptom inventory phobic anxiety subscale


BSIhos            byte     %9.0g                        Basic symptom invenstory hostility subscale


BSIpar            byte     %9.0g                        Basic symptom invenstory Paranoia subscale


BSIpsyc           byte     %9.0g                        Basic symptom inventory Psychoticism subscale score


testage1          double   %9.0g


yrageck           double   %9.0g


iday              byte     %9.0g


idates            str10    %10s


idate             int      %d                           Stata date of interview


bday              byte     %9.0g


bdates            str10    %10s                         String birthdate


bdate             long     %d                           Stata birthdate of respondent


moage             int      %9.0g                        Age of respondent in months


yrage             double   %9.0g                        Computed age of respondent


agerr             double   %9.0g                        Error in age recording?


fenjoyr           byte     %15.0g        fnjr           I no longer enjoy many of the things I used to enjoy (reversal of fenjoy)


fallasr           byte     %15.0g        fnjr           I do not fall alseep easily at night (reversal of ffallas)


MiPTSD            byte     %9.0g                        Misssissipi post-traumatic stress disorder scale


apprxage          int      %9.0g


iyr               int      %9.0g                        Interview year


byr               int      %9.0g                        Birth year


bmo               byte     %9.0g                        Birth month


imo               byte     %9.0g                        Interview month


agemoadj          byte     %9.0g                        Adjustment to age in months


pos               byte     %9.0g                        indicator function


neg               byte     %9.0g                        indicator function


agemo             int      %9.0g                        age in months


ageyrs            double   %9.0g                        computed age of respondent in years


mincumdosew1      double   %8.0g                        wave 1 avg minimum dose of CS137 in mGy ending 12/31/1986


avgcumdosew1      double   %8.0g                        wave 1 avg mean CS137 dose  in mGy ending 12/31/1986


maxcumdosew1      double   %8.0g                        wave2 avg CS137  maximum dose ending 12/31/1986


mincumdosew2      double   %8.0g                        Wave 2 average minimum CS137 dose in mGy ending 12/31/1996


avgcumdosew2      double   %8.0g                        Average mean dose CS1337 in mGy for wave 2


maxcumdosew2      double   %8.0g                        Avg Max dose in mGY for wave 2


mincumdosew3      double   %8.0g                        Wave 3 avg minimum dose of CS137 ending in 12/31/2009


avgcumdosew3      double   %8.0g                        Avg Mean dose of CS137 ending 12/31/2009


maxcumdosew3      double   %8.0g                        Average maximum dose of CS137 ending in 12/31/2009  in mGy


reporttype        str45    %45s                         Report type:


threewavepane~s   str32    %32s                         Three-wave panel, cumulative doses


wave1summary      str10    %10s                         Three-wave panel, cumulative doses


wave2summary      str10    %10s


wave3summary      str10    %10s


ranown2           byte     %27.0g        ranown         Current raion of residence


townnown          byte     %27.0g        townnown       Current town of residence


totltele          long     %9.0g                        Total number of landline phones per raion


area              byte     %22.0g        ar             Basis of sampling weights


areacodewt        int      %9.0g                        Basis of sampling weight


combined          byte     %24.0g        combi          Was this area combined with another to form final sampling weight?


oblnown           byte     %8.0g         oblnown        Current Oblast of residence


numresp           int      %9.0g                        Number of respondents per area


c                 byte     %9.0g                        Constant of unity for subsample computation of cases per area


areaRespid        int      %9.0g                        Number of respondents in sample per areacode


raionwt           double   %9.0g                        inverse of sampling wt per raion


totalphones       long     %9.0g                        Totoal number of phones in Kyiv and Zhitomyr Oblast


sampwt            double   %9.0g                        Sampling weight


fpc1              double   %9.0g                        Finite population correction


cptsd             double   %9.0g                        Mean centered PTSD score


cbdep             double   %9.0g                        Mean centered BSI depression score


cpxd              double   %9.0g                        Mean centered interaction between PTSD and BSI Depression


pxd               int      %9.0g                        Interaction between PTSD and BSI depression


genwt             int      %9.0g                        Post-stratification gender proportion correction factor


agesq             int      %9.0g


male              byte     %9.0g


mar0w3            byte     %9.0g                        Married code 0 in wave 3


emplw35           byte     %8.0g                        emplw3==5. unemployed


occ1w3            byte     %15.0g        LABJ           professional executive administration now


occ2w3            byte     %15.0g        LABJ           technical sales admin support now


occ3w3            byte     %15.0g        LABJ           service occup protective services now


occ4w3            byte     %15.0g        LABJ           precision prod mechan craft construction now


occ5w3            byte     %15.0g        LABJ           factory laborer machinist transp cleaner now


occ6w3            byte     %15.0g        LABJ           farming agricul forestry fishing trapping logging now


occ7w3            byte     %15.0g        LABJ           homemaking or caregiving now


occ8w3            byte     %15.0g        LABJ           student now


inc1w3            byte     %15.0g        LABJ           Income is not sufficient for basic neccessities NOW


inc2w3            byte     %15.0g        LABJ           Income is just sufficient for basic neccessities NOW


inc3w3            byte     %15.0g        LABJ           Income is sufficient for basics plus extra purchases/savings NOW


inc4w3            byte     %15.0g        LABJ           Income allows to comfortably afford luxury items NOW


radhlw3           byte     %8.0g                        Self-perceived Chornobyl health threat in wave 3


radchw3           byte     %8.0g                        believed % of polution related to chornobyl NOW


radtlw3           byte     %8.0g                        believed % of cumulative radiation exposed to in a lifetime NOW


havmil            double   %9.0g                        Distance from Chornobyl in miles


bfmEL2            float    %9.0g                         max(0, 21928 - BSIsoma)


bfmEL4            float    %9.0g                         max(0, 21988 - BSIposymp)


bfmEL16           float    %9.0g                         max(0, 22136 - kmacc)


carcin            byte     %8.0g                    *   a person exposed to carcinogen  is likely to get cancer (% of agreement)


healthef          byte     %8.0g                    *   a person exposed to any radiation  likely to suffer from (% of agreement)


dvcew3            byte     %8.0g                        Total number of divorces experienced in time period 1996-NOW


sepaw3            byte     %8.0g                        Total number of separations experienced in time period 1996-NOW


shhlw3            byte     %8.0g                        Percentage of strains and hassles related to health NOW


shhousw3          byte     %8.0g                        Percentage of strains and hassles related to housing NOW


phlthw3           byte     %8.0g                        level of general physical health now


suprtw3           byte     %8.0g                        Level of support (in percent) from partner NOW


fdferw3           byte     %8.0g                    *   level of fear in percent from consuming foods contaminated with radiation in 199


dafter            int      %8.0g                    *   how many days lapsed after Chornobyl accident before you heard about the acciden


near              byte     %8.0g                    *   radiation from a nuclear plant site is more concentrated near the plant (% of ag


chsize            byte     %8.0g                    *   the radioactive fallout from chornobyl affected more people than the radioactive


polprw3           byte     %8.0g                        consider hazardous (in percent) - political problems NOW


icdxcnt           byte     %9.0g                        count of icdx illnesses


. set more off

. regress WHPel age educ2-educ7 marrw31-marrw33 marrw35 childw3 ///
>   emplw32-emplw34 occ1w3-occ7w3 inc1w3-inc4w3 radhlw3 radchw3 ///
>   radtlw3 havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     dvcew3 sepaw3 ///
>    shhlw3 shhousw3 phlthw3 suprtw3 fdferw3 ///
>    dafter near chsize polprw3 icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     338
                                                       F( 47,   337) =   14.82
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4257
                                                       Root MSE      =  24.553

(Std. Err. adjusted for 338 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .0903385    .1627891      0.55    0.579     -.2298724     .4105493
       educ2 |    11.47363    16.78883      0.68    0.495     -21.55048     44.49774
       educ3 |    15.29007    15.70656      0.97    0.331     -15.60517     46.18532
       educ4 |    10.53389    16.42481      0.64    0.522     -21.77418     42.84196
       educ5 |    25.27605    15.66273      1.61    0.108     -5.532993     56.08509
       educ6 |    21.14131    15.53762      1.36    0.175     -9.421621     51.70424
       educ7 |    20.02427    19.45404      1.03    0.304     -18.24237     58.29092
     marrw31 |    3.482547    10.04415      0.35    0.729     -16.27458     23.23967
     marrw32 |   -3.840648    10.66769     -0.36    0.719     -24.82429     17.14299
     marrw33 |    2.532121    10.24481      0.25    0.805      -17.6197     22.68395
     marrw35 |   -4.499927    11.64662     -0.39    0.699     -27.40915     18.40929
     childw3 |   -.5478584    1.839036     -0.30    0.766     -4.165294     3.069578
     emplw32 |    6.148683    4.514167      1.36    0.174     -2.730811     15.02818
     emplw33 |    1.605113    7.718013      0.21    0.835     -13.57644     16.78666
     emplw34 |   -9.812303    6.955411     -1.41    0.159     -23.49379     3.869188
      occ1w3 |   -3.287587     13.9735     -0.24    0.814     -30.77385     24.19868
      occ2w3 |   -7.013005    14.26619     -0.49    0.623     -35.07501     21.04899
      occ3w3 |    5.198289    14.54013      0.36    0.721     -23.40256     33.79914
      occ4w3 |   -.3815392    14.43193     -0.03    0.979     -28.76955     28.00647
      occ5w3 |    12.49805    15.23592      0.82    0.413     -17.47143     42.46753
      occ6w3 |    8.412501    18.86591      0.45    0.656     -28.69727     45.52228
      occ7w3 |   -1.342951    14.99661     -0.09    0.929      -30.8417      28.1558
      inc1w3 |   -.0525973    13.87179     -0.00    0.997      -27.3388     27.23361
      inc2w3 |   -.5557414    12.91364     -0.04    0.966     -25.95724     24.84576
      inc3w3 |    .3949606    12.97367      0.03    0.976     -25.12461     25.91453
      inc4w3 |   -4.791595    14.46611     -0.33    0.741     -33.24684     23.66365
     radhlw3 |    .0197592    .0642891      0.31    0.759     -.1066992     .1462177
     radchw3 |    .0894927    .0584249      1.53    0.127     -.0254307     .2044162
     radtlw3 |     .014993    .0543891      0.28    0.783      -.091992     .1219779
      havmil |    .0498563     .029365      1.70    0.090     -.0079055      .107618
      bfmEL2 |   -1.429926    .5892686     -2.43    0.016     -2.589034    -.2708179
      bfmEL4 |   -.3690884    .1374577     -2.69    0.008     -.6394715    -.0987052
     bfmEL16 |    .0493683    .0184824      2.67    0.008       .013013     .0857237
      carcin |   -.4263463    .1536463     -2.77    0.006      -.728573    -.1241196
    healthef |     .379718    .1662925      2.28    0.023       .052616     .7068199
      dvcew3 |   -3.503823    8.937278     -0.39    0.695      -21.0837     14.07606
      sepaw3 |    10.28718    11.18044      0.92    0.358     -11.70506     32.27941
      shhlw3 |   -.0533874     .053445     -1.00    0.319     -.1585152     .0517404
    shhousw3 |    .0298894    .0592072      0.50    0.614     -.0865728     .1463515
     phlthw3 |   -.1410255    .0912887     -1.54    0.123      -.320593     .0385419
     suprtw3 |   -.0067075    .0522928     -0.13    0.898      -.109569     .0961539
     fdferw3 |   -.0547576    .0755596     -0.72    0.469     -.2033855     .0938703
      dafter |   -.0111606    .0173403     -0.64    0.520     -.0452694     .0229482
        near |   -.1306345    .0468761     -2.79    0.006     -.2228411     -.038428
      chsize |   -.1598153    .0512622     -3.12    0.002     -.2606495     -.058981
     polprw3 |   -.0492439    .0467265     -1.05    0.293     -.1411562     .0426683
     icdxcnt |    3.188591     1.10104      2.90    0.004      1.022814     5.354368
       _cons |    38366.03    11222.48      3.42    0.001       16291.1     60440.96
-------------+----------------------------------------------------------------

.
. scalar fw3wbf = e(r2_a)

.
. title "Wave 3 trimmed male" "dose energy level response model with basis functions"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****                        Wave 3 trimmed male                          *****
*****       dose energy level response model with basis functions         *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:27  *****
*******************************************************************************
*******************************************************************************


. des WHPel age educ2-educ7 emplw32-emplw34  radchw3 ///
>     bfmEL2 bfmEL4 bfmEL16 carcin healthef near chsize icdxcnt

              storage  display     value
variable name   type   format      label      variable label
-------------


WHPel             double   %9.0g                        Wtd Health Profile Pt 1 Energy Level Subscale


age               byte     %8.0g                    *   Respondent's age


educ2             byte     %8.0g                        educ==2. graduated high school


educ3             byte     %8.0g                        educ==3. technical degree


educ4             byte     %8.0g                        educ==4. did not finish college/bachelor's


educ5             byte     %8.0g                        educ==5. graduated college/bachelor's


educ6             byte     %8.0g                        educ==6. finished specialist/master's degree


educ7             byte     %8.0g                        educ==7. doctor of science/phd


emplw32           byte     %8.0g                        emplw3==2. part time


emplw33           byte     %8.0g                        emplw3==4. retired


emplw34           byte     %8.0g                        emplw3==5. unemployed


radchw3           byte     %8.0g                        believed % of polution related to chornobyl NOW


bfmEL2            float    %9.0g                         max(0, 21928 - BSIsoma)


bfmEL4            float    %9.0g                         max(0, 21988 - BSIposymp)


bfmEL16           float    %9.0g                         max(0, 22136 - kmacc)


carcin            byte     %8.0g                    *   a person exposed to carcinogen  is likely to get cancer (% of agreement)


healthef          byte     %8.0g                    *   a person exposed to any radiation  likely to suffer from (% of agreement)


near              byte     %8.0g                    *   radiation from a nuclear plant site is more concentrated near the plant (% of ag


chsize            byte     %8.0g                    *   the radioactive fallout from chornobyl affected more people than the radioactive


icdxcnt           byte     %9.0g                        count of icdx illnesses


.
. set more off

. regress WHPel age educ2-educ7  ///
>   emplw32-emplw34  radchw3 ///
>     bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>    near chsize icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 19,   339) =   12.18
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3808
                                                       Root MSE      =  24.291

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .1217102    .1464617      0.83    0.407     -.1663779     .4097983
       educ2 |    22.37493    12.72676      1.76    0.080      -2.65844      47.4083
       educ3 |    22.23436     11.9254      1.86    0.063     -1.222748     45.69146
       educ4 |    19.34461    12.60499      1.53    0.126     -5.449241     44.13845
       educ5 |    28.34069    12.06047      2.35    0.019      4.617914     52.06346
       educ6 |    24.73449      12.011      2.06    0.040       1.10902     48.35995
       educ7 |    25.95312    15.73915      1.65    0.100     -5.005564     56.91181
     emplw32 |    5.905683    4.066576      1.45    0.147     -2.093217     13.90458
     emplw33 |    3.701983    4.812305      0.77    0.442     -5.763757     13.16772
     emplw34 |   -6.054123    4.562305     -1.33    0.185     -15.02812     2.919869
     radchw3 |    .1114297     .047236      2.36    0.019      .0185171     .2043423
      bfmEL2 |   -1.445295    .5426682     -2.66    0.008     -2.512716    -.3778742
      bfmEL4 |   -.4035927    .1263098     -3.20    0.002     -.6520424    -.1551429
     bfmEL16 |    .0164658    .0069007      2.39    0.018      .0028922     .0300395
      carcin |   -.5208226    .1145601     -4.55    0.000     -.7461607    -.2954845
    healthef |    .4341559    .1311484      3.31    0.001      .1761887      .692123
        near |   -.1360871    .0431014     -3.16    0.002     -.2208669    -.0513072
      chsize |   -.1396909    .0502899     -2.78    0.006     -.2386106    -.0407713
     icdxcnt |    3.082991     .985552      3.13    0.002      1.144424     5.021559
       _cons |    40163.87    9958.671      4.03    0.000       20575.3     59752.44
-------------+----------------------------------------------------------------

. scalar tw3bf = e(r2_a)

. scalar list tw3bf
     tw3bf =  .34404231

.
. set more off

. regress WHPel age educ2-educ7  ///
>   emplw32-emplw34  radchw3 ///
>    carcin healthef ///
>    near chsize icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 16,   339) =    7.71
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1764
                                                       Root MSE      =  27.884

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |      .36425     .172106      2.12    0.035      .0257197     .7027802
       educ2 |    19.62489    8.144793      2.41    0.017      3.604196     35.64559
       educ3 |     24.8153    6.549382      3.79    0.000      11.93275     37.69784
       educ4 |    20.87239    9.254133      2.26    0.025      2.669636     39.07515
       educ5 |    29.14607    7.408083      3.93    0.000      14.57447     43.71767
       educ6 |    24.80881    6.604278      3.76    0.000      11.81828     37.79933
       educ7 |    14.20245    12.05288      1.18    0.239     -9.505396      37.9103
     emplw32 |    5.040772    5.101898      0.99    0.324     -4.994592     15.07614
     emplw33 |    7.636472    5.438431      1.40    0.161     -3.060848     18.33379
     emplw34 |   -5.748799    6.149031     -0.93    0.350     -17.84386     6.346262
     radchw3 |     .029516    .0484145      0.61    0.543     -.0657147     .1247467
      carcin |   -.5962181     .146627     -4.07    0.000     -.8846314    -.3078048
    healthef |     .616168    .1620102      3.80    0.000      .2974962     .9348399
        near |   -.0407626    .0488878     -0.83    0.405     -.1369242      .055399
      chsize |   -.0915662    .0641135     -1.43    0.154     -.2176766     .0345442
     icdxcnt |    4.644165    1.122234      4.14    0.000      2.436746     6.851584
       _cons |   -24.76154    12.84988     -1.93    0.055     -50.03707     .5139894
-------------+----------------------------------------------------------------

.
. title "Wave 3 male energy level Moderator analysis"


*******************************************************************************
*******************************************************************************
*****                                                                     *****
*****                                                                     *****
*****            Wave 3 male energy level Moderator analysis              *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:27  *****
*******************************************************************************
*******************************************************************************


.
.
.
. * trimmed wave 3 male model
.
.  regress WHPel age educ2-educ7  ///
>   emplw32-emplw34  radchw3 ///
>     bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>    near chsize icdxcnt if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 19,   339) =   12.18
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3808
                                                       Root MSE      =  24.291

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .1217102    .1464617      0.83    0.407     -.1663779     .4097983
       educ2 |    22.37493    12.72676      1.76    0.080      -2.65844      47.4083
       educ3 |    22.23436     11.9254      1.86    0.063     -1.222748     45.69146
       educ4 |    19.34461    12.60499      1.53    0.126     -5.449241     44.13845
       educ5 |    28.34069    12.06047      2.35    0.019      4.617914     52.06346
       educ6 |    24.73449      12.011      2.06    0.040       1.10902     48.35995
       educ7 |    25.95312    15.73915      1.65    0.100     -5.005564     56.91181
     emplw32 |    5.905683    4.066576      1.45    0.147     -2.093217     13.90458
     emplw33 |    3.701983    4.812305      0.77    0.442     -5.763757     13.16772
     emplw34 |   -6.054123    4.562305     -1.33    0.185     -15.02812     2.919869
     radchw3 |    .1114297     .047236      2.36    0.019      .0185171     .2043423
      bfmEL2 |   -1.445295    .5426682     -2.66    0.008     -2.512716    -.3778742
      bfmEL4 |   -.4035927    .1263098     -3.20    0.002     -.6520424    -.1551429
     bfmEL16 |    .0164658    .0069007      2.39    0.018      .0028922     .0300395
      carcin |   -.5208226    .1145601     -4.55    0.000     -.7461607    -.2954845
    healthef |    .4341559    .1311484      3.31    0.001      .1761887      .692123
        near |   -.1360871    .0431014     -3.16    0.002     -.2208669    -.0513072
      chsize |   -.1396909    .0502899     -2.78    0.006     -.2386106    -.0407713
     icdxcnt |    3.082991     .985552      3.13    0.002      1.144424     5.021559
       _cons |    40163.87    9958.671      4.03    0.000       20575.3     59752.44
-------------+----------------------------------------------------------------

.
.   foreach var in radchw3 bfmEL2 bfmEL4 bfmEL16 carcin healthef near chsize icdxcnt {
  2.   cap gen `var'Xd3 = `var'*avgcumdosew3
  3.   }

.
.  regress WHPel age educ2-educ7  ///
>   emplw32-emplw34  radchw3 ///
>     bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>    near chsize icdxcnt radchw3Xd3-icdxcntXd3 if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 27,   339) =   16.60
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4401
                                                       Root MSE      =  23.392

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .0330411    .1389867      0.24    0.812     -.2403439     .3064261
       educ2 |    23.87239    13.24576      1.80    0.072      -2.18184     49.92662
       educ3 |    23.76199    12.50738      1.90    0.058     -.8398631     48.36384
       educ4 |    20.33195    13.31649      1.53    0.128       -5.8614     46.52531
       educ5 |    28.20355    12.69004      2.22    0.027      3.242402     53.16469
       educ6 |    24.80417    12.52745      1.98    0.049      .1628516     49.44548
       educ7 |    28.71336    16.16683      1.78    0.077     -3.086569     60.51329
     emplw32 |    7.366042    4.040703      1.82    0.069     -.5819665     15.31405
     emplw33 |    4.989851    4.645205      1.07    0.283     -4.147204     14.12691
     emplw34 |   -6.368773    4.923183     -1.29    0.197     -16.05261     3.315062
     radchw3 |    .3213555    .0661095      4.86    0.000      .1913191     .4513919
      bfmEL2 |   -1.825621    .5354342     -3.41    0.001     -2.878813     -.772429
      bfmEL4 |   -.2912571    .1428472     -2.04    0.042     -.5722356    -.0102787
     bfmEL16 |     .014572    .0075064      1.94    0.053     -.0001931      .029337
      carcin |   -.0531967    .5098793     -0.10    0.917     -1.056122      .949729
    healthef |   -.0928404    .5166795     -0.18    0.858     -1.109142     .9234612
        near |   -.0894721      .05657     -1.58    0.115     -.2007445     .0218003
      chsize |   -.1635135    .0499294     -3.27    0.001     -.2617241     -.065303
     icdxcnt |    3.067216    1.225662      2.50    0.013      .6563565     5.478076
  radchw3Xd3 |   -.2069428    .0478594     -4.32    0.000     -.3010815     -.112804
   bfmEL2Xd3 |    .0890891    .0673933      1.32    0.187     -.0434726     .2216507
   bfmEL4Xd3 |   -.0821843    .0591057     -1.39    0.165     -.1984444     .0340759
  bfmEL16Xd3 |   -.0064216    .0122562     -0.52    0.601     -.0305294     .0176863
   carcinXd3 |   -.9222289    1.209749     -0.76    0.446     -3.301788     1.457331
 healthefXd3 |    .9904612    1.211948      0.82    0.414     -1.393423     3.374346
     nearXd3 |   -.0473981    .0366268     -1.29    0.197     -.1194424     .0246463
  icdxcntXd3 |    .4058024    .6463428      0.63    0.531     -.8655452      1.67715
       _cons |     46072.3    9745.201      4.73    0.000      26903.62     65240.98
-------------+----------------------------------------------------------------

.
.
.  * there may have been one moderator effect in wave three:  of radchw3Xd3 on Energy level
.  centile radchw3 if gender==1, centile(33 67)

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
     radchw3 |      340        33            30              20          30
             |                 67            60              50          70

.  * our cut points are radchw3 = 30 and radchw3 = 60
.
.  cap gen lowPoldose = avgcumdosew1 if radchw3 <= 30 & gender==1

. cap gen midPoldose = avgcumdosew1 if radchw3 > 30 & radchw3 < 60 & gender==1

. cap gen hiPoldose = avgcumdosew1 if radchw3  >= 60  & radchw3 < . & gender==1

.
. twoway lfit WHPel lowPoldose || lfit WHPel midPoldose || lfit WHPel hiPoldose, ///
>    title("Effect of belief in % pollution due to Chornobyl" "by dose on Energy level in wave 3") ///
>      xti(average cumulative wave 3 dose of {superscript:137}CS in milliGrays)  ///
>      ytitle(Energy level) lcolor(red green blue) lpattern(dash longdash solid) ///
>      legend(label(1 "1/3 or less of pollution due to Chornobyl") label(2 "1/3 to 2/3 of pollution due to Chornobyl") ///
>      label(3 "more than 2/3 pollution ndue to Chornobyl") rows(3))

. graph save ElpctpoltXdosew3.gph, replace
(file ElpctpoltXdosew3.gph saved)

. graph export ELpctpolXdosew3.eps, replace
(file ELpctpolXdosew3.eps written in EPS format)

.
.
.
.
.
. scalar tw3nobf = e(r2_a)

. scalar list tw3nobf
   tw3nobf =  .39169032

.
. // r2 without bf = .153
.
.
. scalar tw3bfw3 = e(r2_a)

.
.
. // r2 with bf = .3109
.
. // r2 due to bf = .1579
.
. // comparison model is identical r2 : here we substituted the components
.
.
. scalar w3numbf = 3

.
. scalar r2chabfw3 = tw3bf - tw3nobf

. scalar avgImpBF = r2chabfw3/w3numbf

. scalar numModsw3 = 1

. scalar numMedsw3 = 4

.
. scalar list
W2maleELmed = age radfmw3 sleep, illww3 and Hp2sxlife
W2maleELMed = age and hp2sxlife
W1MaleELMed = radhlw1 and depagw1
w1maleELmods = age suprtw1 fdferw1 chsizew1 icdxcnt
w1numbmaleELmods =          5
w1numaleElmods =          5
 r2chabfw1 =  .07938894
     twbf2 =  .48490811
    twnobf =  .26459544
FemPainDoseMedsw3 = age illw3 phlthw3 radfmw3 hospw3 and radhlw3
    badout =          0
    ckcrit =  .31764707
  pctvalid =       62.5
pctinvalid =       37.5
 numMedFw2 =          1
FemPainW2Med = age
numbfsigfw2 =          9
   dsigfw2 =          0
       fw2 =  .57745936
FemPainW1Meds = educ and age
numModsigFw1 =          0
numbfsigfw1 =          1
numMainEffsigFw1 =          5
   dsigfw1 =          0
numMedPainDoseFsigw3 =          6
numbfsigTw3 =         15
numModsigTw3 =          0
numModsigFw3 =          0
numbfsigfw3 =         15
   dsigtw3 =          0
 numMedFw3 =         15
numMainEffsigTw3 =         16
   dsigfw3 =          0
numMainEffsigFw3 =         16
       fw3 =  .63678289
numbfsigtw2 =          0
 numMedMw2 =          2
   w2numbf =          7
numbfsigTw2 =          9
   tw2nobf =  .26459544
numModsigTw2 =          3
     tw2bf =  .29409811
numMainEffsigTw2 =          5
   dsigtw2 =          0
numbfsigMw2 =          0
numModsigFw2 =          2
numbfsigFw2 =          3
numMainEffsigFw2 =          8
   dsigFw2 =         .5
       mw2 =  .35574302
numModsigTw1 =          1
numMainEffsigTw1 =          5
numModsigMw1 =          0
   dsigtw1 =          3
numbfsigtw1 =          2
NumMainEffsigTw1 =         11
numbfsigMw1 =          1
numMainEffsigMw1 =          7
       Mw1 =  .28222811
   dsigMw1 =          1
        wv =          3
        pt =          1
       hyp =          1
W2FemaleELmed = age radfmw3 BSIanx BSIdep icdxcnt radhlw3 illw3 and Hp2sxlife
 numMedsw3 =          4
 numModsw3 =          1
  avgImpBF = -.01588267
 r2chabfw3 = -.04764801
   w3numbf =          3
   tw3bfw3 =  .39169032
W2FemaleELMed = age and radfmw2 radhlw2 radchw2 illw2 BSIanx BSIdep icdxcnt hp2sxlife
   tw3nobf =  .39169032
     tw3bf =  .34404231
    fw3wbf =  .33260096
 numMedsw2 =          2
   tw2bfw2 =  .48481206
avgImpBFw2 =  .07519191
 r2chabfw2 =  .22557574
 NumMedsw2 =          2
 numModsw2 =          0
 w2numbfw2 =          3
 tw2nobfw2 =   .1308152
  tw2wbfw2 =  .35639094
  fw2wbfw2 =  .34555619
W1numMELMeds =          2
W1FemaleELMed = age icdxcnt BSIdep depagw1 BSIanx anxagw1 PTSDw1 HP2sxlife
w1numMElMeds =          2
w1nuFemaleElmods =          0
avgImpBFw1 =  .05367898
   w1numbf =          3
   r2chabf =  .16103694
   tw1nobf =  .18797502
     tw1bf =  .34901196
       fw1 =  .37964479

. matrix define MaleWHPelr2w3 = (fw3, tw3bf, tw3nobf, w3numbf,  r2chabfw3, avgImpBF, numModsw3, numMedsw3)

. matrix colnames MaleWHPelr2w3 = FullBFR2a TR2aBF  TR2aNoBF  NumBF  BFR2cha avgImpBF numModsw3 numMedsw3

. matrix rownames MaleWHPelr2w3 = wave3

. matlist MaleWHPelr2w3

   | FullBFR2a    TR2aBF    TR2aNoBF    NumBF    BFR2cha    avgImpBF    numModsw3    numMedsw3
-------------+----------------------------------------------------------------------------------------
wave3   |  .6367829     .3440423     .3916903            3     -.047648    -.0158827            1            4

.
. matrix define MaleWHPelr2 = (MaleWHPelr2w1 \ MaleWHPelr2w2 \ MaleWHPelr2w3 )

. matlist MaleWHPelr2

   | FullBFR2a    TR2aBF    TR2aNoBF    NumBF    BFR2cha    AvgImpBF    w1numMods    w1numMeds
-------------+----------------------------------------------------------------------------------------
wave1   |  .3796448      .349012      .187975            3     .1610369      .053679            5            2
wave2   |  .5774594     .4848121     .1308152            3     .2255757     .0751919            5            2
wave3   |  .6367829     .3440423     .3916903            3     -.047648    -.0158827            1            4

.
.
.
. title "Wave 3 male mediation analysis"


*******************************************************************************
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*****                                                                     *****
*****                                                                     *****
*****                   Wave 3 male mediation analysis                    *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:29  *****
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.
. title "age, threat to family,  illness during wave 3, and sex life" "are possible male mediators of energy level in wave 3"


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*****                                                                     *****
*****                                                                     *****
*****    age, threat to family,  illness during wave 3, and sex life      *****
*****       are possible male mediators of energy level in wave 3         *****
*****                                                                     *****
*****                                                                     *****
*****                                            29 Jun 2012    07:48:29  *****
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*******************************************************************************


.
. cap gen whpel = WHPel

. sem(avgcumdosew3->age)(age->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  age whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3772.2384
Iteration 1:   log likelihood = -3772.2384

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3772.2384

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   age <-         |
    avgcumdosew3 |    .5433648    .2465374      2.20    0.028      .0601605     1.026569
           _cons |    48.52021    .7226029     67.15    0.000      47.10394     49.93649
  ---------------+----------------------------------------------------------------
   whpel <-       |
             age |    .6520247    .1282979      5.08    0.000      .4005655     .9034839
           _cons |   -8.877521    6.501358     -1.37    0.172     -21.61995     3.864907
-----------------+----------------------------------------------------------------
 Variance         |
           e.age |    146.8453    11.26252                    126.3501     170.6649
         e.whpel |    833.5635     63.9314                    717.2235     968.7748
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.19, Prob > chi2 = 0.0227

. sem(avgcumdosew3->illw3)(illw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  illw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood =  -2908.831
Iteration 1:   log likelihood =  -2908.831

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -2908.831

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   illw3 <-       |
    avgcumdosew3 |     .038211    .0191573      1.99    0.046      .0006633     .0757587
           _cons |    .4504952    .0561503      8.02    0.000      .3404427     .5605478
  ---------------+----------------------------------------------------------------
   whpel <-       |
           illw3 |    6.444621    1.678832      3.84    0.000      3.154171     9.735072
           _cons |    19.98723    1.795737     11.13    0.000      16.46765     23.50681
-----------------+----------------------------------------------------------------
 Variance         |
         e.illw3 |    .8866751    .0680049                    .7629223     1.030502
         e.whpel |    859.6273    65.93041                    739.6496     999.0665
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.88, Prob > chi2 = 0.0153

. sem(avgcumdosew3->radchw3)(radchw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radchw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood =  -4130.718
Iteration 1:   log likelihood =  -4130.718

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -4130.718

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radchw3 <-     |
    avgcumdosew3 |    .6454152    .6824406      0.95    0.344     -.6921437     1.982974
           _cons |    45.17233    2.000238     22.58    0.000      41.25193     49.09272
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radchw3 |    .0257932    .0483353      0.53    0.594     -.0689423     .1205286
           _cons |    22.00517    2.751446      8.00    0.000      16.61243      27.3979
-----------------+----------------------------------------------------------------
 Variance         |
       e.radchw3 |    1125.185    86.29778                    968.1438       1307.7
         e.whpel |    896.1341    68.73035                    771.0611     1041.495
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.55, Prob > chi2 = 0.0060

. sem(avgcumdosew3->radhlw3)(radhlw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radhlw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -4134.7323
Iteration 1:   log likelihood = -4134.7323

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4134.7323

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radhlw3 <-     |
    avgcumdosew3 |    .9606492    .7203412      1.33    0.182     -.4511936     2.372492
           _cons |    46.19995    2.111326     21.88    0.000      42.06183     50.33807
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radhlw3 |    .2412601    .0438412      5.50    0.000      .1553329     .3271873
           _cons |    11.76196    2.595225      4.53    0.000      6.675408      16.8485
-----------------+----------------------------------------------------------------
 Variance         |
       e.radhlw3 |    1253.634    96.14937                    1078.665     1456.985
         e.whpel |    823.5333    63.16212                    708.5932     957.1177
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.23, Prob > chi2 = 0.0126

. sem(avgcumdosew3->icdxcnt)(icdxcnt->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  icdxcnt whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3091.7606
Iteration 1:   log likelihood = -3091.7606

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3091.7606

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   icdxcnt <-     |
    avgcumdosew3 |    .0494693    .0341865      1.45    0.148     -.0175351     .1164736
           _cons |    2.083835    .1002009     20.80    0.000      1.887445     2.280225
  ---------------+----------------------------------------------------------------
   whpel <-       |
         icdxcnt |    6.082854    .9053643      6.72    0.000      4.308372     7.857335
           _cons |    10.14823    2.469212      4.11    0.000      5.308668      14.9878
-----------------+----------------------------------------------------------------
 Variance         |
       e.icdxcnt |    2.823605    .2165606                    2.429516     3.281619
         e.whpel |    791.7647    60.72558                    681.2585     920.1959
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.87, Prob > chi2 = 0.0154

. sem(avgcumdosew3->BSIdep)(BSIdep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIdep whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3271.6012
Iteration 1:   log likelihood = -3271.6012

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3271.6012

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIdep <-      |
    avgcumdosew3 |    .0604859    .0582607      1.04    0.299      -.053703     .1746748
           _cons |    8.058645    .1707626     47.19    0.000      7.723957     8.393334
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIdep |    3.684326    .5298397      6.95    0.000       2.64586     4.722793
           _cons |   -6.771654    4.568981     -1.48    0.138     -15.72669     2.183384
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIdep |    8.200603    .6289576                     7.05605     9.530814
         e.whpel |    785.2146    60.22321                    675.6226     912.5834
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      6.60, Prob > chi2 = 0.0102

. sem(avgcumdosew3->BSIanx)(BSIanx->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  BSIanx whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3253.1084
Iteration 1:   log likelihood = -3253.1084

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3253.1084

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   BSIanx <-      |
    avgcumdosew3 |    .0894878     .056116      1.59    0.111     -.0204976     .1994732
           _cons |    7.511539    .1644766     45.67    0.000      7.189171     7.833907
  ---------------+----------------------------------------------------------------
   whpel <-       |
          BSIanx |    4.239198     .539721      7.85    0.000      3.181364     5.297031
           _cons |   -9.114591     4.37601     -2.08    0.037     -17.69141    -.5377688
-----------------+----------------------------------------------------------------
 Variance         |
        e.BSIanx |    7.607966    .5835044                    6.546127     8.842046
         e.whpel |    759.1408    58.22344                    653.1879     882.2802
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.45, Prob > chi2 = 0.0195

. sem(avgcumdosew3->PTSDw3)(PTSDw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  PTSDw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3776.1898
Iteration 1:   log likelihood = -3776.1898

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3776.1898

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   PTSDw3 <-      |
    avgcumdosew3 |    .0190223    .2434295      0.08    0.938     -.4580907     .4961354
           _cons |    5.205553    .7134937      7.30    0.000      3.807131     6.603974
  ---------------+----------------------------------------------------------------
   whpel <-       |
          PTSDw3 |    .3901717    .1340795      2.91    0.004      .1273806     .6529627
           _cons |    21.15048    1.750796     12.08    0.000      17.71899     24.58198
-----------------+----------------------------------------------------------------
 Variance         |
        e.PTSDw3 |    143.1663    10.98035                    123.1846     166.3891
         e.whpel |    875.0895     67.1163                    752.9537     1017.037
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.80, Prob > chi2 = 0.0052

. sem(avgcumdosew3->radfmw3)(radfmw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radfmw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -4130.4495
Iteration 1:   log likelihood = -4130.4495

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4130.4495

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radfmw3 <-     |
    avgcumdosew3 |    1.581248    .7074787      2.24    0.025      .1946154     2.967881
           _cons |    54.80546    2.073626     26.43    0.000      50.74123     58.86969
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radfmw3 |    .2290481    .0446712      5.13    0.000      .1414942     .3166021
           _cons |    10.19615    2.978464      3.42    0.001      4.358465     16.03383
-----------------+----------------------------------------------------------------
 Variance         |
       e.radfmw3 |    1209.264    92.74633                    1040.488     1405.418
         e.whpel |    832.5108    63.85067                    716.3177     967.5514
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      5.14, Prob > chi2 = 0.0234

. sem(avgcumdosew3->radtlw3)(radtlw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  radtlw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -4144.7956
Iteration 1:   log likelihood = -4144.7956

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4144.7956

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   radtlw3 <-     |
    avgcumdosew3 |    .6410208    .7122484      0.90    0.368     -.7549604     2.037002
           _cons |    50.51592    2.087605     24.20    0.000      46.42429     54.60755
  ---------------+----------------------------------------------------------------
   whpel <-       |
         radtlw3 |    .0507232    .0462559      1.10    0.273     -.0399366     .1413831
           _cons |    20.58864    2.873801      7.16    0.000      14.95609     26.22118
-----------------+----------------------------------------------------------------
 Variance         |
       e.radtlw3 |    1225.624    94.00109                    1054.565     1424.431
         e.whpel |    893.7238    68.54548                    768.9872     1038.694
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.42, Prob > chi2 = 0.0065

. sem(avgcumdosew3->anxagw3)(anxagw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  anxagw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3931.4484
Iteration 1:   log likelihood = -3931.4484

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3931.4484

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   anxagw3 <-     |
    avgcumdosew3 |   -.0782166    .3841032     -0.20    0.839      -.831045     .6746118
           _cons |    10.00233    1.125809      8.88    0.000      7.795782     12.20887
  ---------------+----------------------------------------------------------------
   whpel <-       |
         anxagw3 |    .2416475    .0850174      2.84    0.004      .0750165     .4082786
           _cons |    20.79658    1.812757     11.47    0.000      17.24365     24.34952
-----------------+----------------------------------------------------------------
 Variance         |
       e.anxagw3 |    356.4431    27.33794                    306.6946     414.2614
         e.whpel |    876.0681    67.19136                    753.7958     1018.174
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      8.04, Prob > chi2 = 0.0046

. sem(avgcumdosew3->HP2sxlife)(HP2sxlife->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  HP2sxlife whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood =  -2603.316
Iteration 1:   log likelihood =  -2603.316

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    =  -2603.316

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   HP2sxlife <-   |
    avgcumdosew3 |    .0181247    .0081232      2.23    0.026      .0022035     .0340458
           _cons |    .1808546    .0238091      7.60    0.000      .1341896     .2275197
  ---------------+----------------------------------------------------------------
   whpel <-       |
       HP2sxlife |    25.39498    3.796194      6.69    0.000      17.95458     32.83539
           _cons |     18.0369    1.710147     10.55    0.000      14.68507     21.38873
-----------------+----------------------------------------------------------------
 Variance         |
     e.HP2sxlife |    .1594218    .0122271                    .1371714     .1852814
         e.whpel |    792.5673    60.78714                    681.9491     921.1287
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      4.62, Prob > chi2 = 0.0316

. sem(avgcumdosew3->drinkspww3)(drinkspww3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  drinkspww3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3213.6951
Iteration 1:   log likelihood = -3213.6951

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3213.6951

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   drinkspww3 <-  |
    avgcumdosew3 |    -.013162    .0460949     -0.29    0.775     -.1035063     .0771823
           _cons |    2.038437    .1351044     15.09    0.000      1.773637     2.303237
  ---------------+----------------------------------------------------------------
   whpel <-       |
      drinkspww3 |   -.9465378    .7149247     -1.32    0.186     -2.347764     .4546889
           _cons |    25.10486    2.171378     11.56    0.000      20.84904     29.36069
-----------------+----------------------------------------------------------------
 Variance         |
    e.drinkspww3 |    5.133335    .3937088                    4.416878     5.966008
         e.whpel |    892.2844    68.43509                    767.7488     1037.021
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.60, Prob > chi2 = 0.0058

. sem(avgcumdosew3->depagw3)(depagw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  depagw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3902.6711
Iteration 1:   log likelihood = -3902.6711

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3902.6711

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   depagw3 <-     |
    avgcumdosew3 |   -.0455259    .3570454     -0.13    0.899     -.7453221     .6542702
           _cons |    9.564527    1.046503      9.14    0.000       7.51342     11.61564
  ---------------+----------------------------------------------------------------
   whpel <-       |
         depagw3 |    .3643646    .0904096      4.03    0.000       .187165     .5415642
           _cons |    19.72583     1.80464     10.93    0.000       16.1888     23.26286
-----------------+----------------------------------------------------------------
 Variance         |
       e.depagw3 |    307.9933    23.62201                    265.0069     357.9526
         e.whpel |     855.993    65.65167                    736.5225     994.8426
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      8.21, Prob > chi2 = 0.0042

. sem(avgcumdosew3->whpsleep)(whpsleep->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  whpsleep whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3986.3067
Iteration 1:   log likelihood = -3986.3067

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3986.3067

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   whpsleep <-    |
    avgcumdosew3 |    1.000935     .501409      2.00    0.046      .0181913     1.983679
           _cons |    16.07715    1.469634     10.94    0.000      13.19672     18.95758
  ---------------+----------------------------------------------------------------
   whpel <-       |
        whpsleep |     .551618    .0582892      9.46    0.000      .4373733     .6658628
           _cons |    13.64932    1.761942      7.75    0.000      10.19597     17.10266
-----------------+----------------------------------------------------------------
 Variance         |
      e.whpsleep |    607.4055    46.58587                    522.6302      705.932
         e.whpel |    709.8956    54.44651                    610.8158     825.0469
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      4.39, Prob > chi2 = 0.0361

. sem(avgcumdosew3->fdferw3)(fdferw3->whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  fdferw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -4040.0094
Iteration 1:   log likelihood = -4040.0094

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -4040.0094

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   fdferw3 <-     |
    avgcumdosew3 |    .1781849     .532393      0.33    0.738     -.8652861     1.221656
           _cons |    13.51816    1.560448      8.66    0.000      10.45974     16.57658
  ---------------+----------------------------------------------------------------
   whpel <-       |
         fdferw3 |    .2204663    .0608924      3.62    0.000      .1011194     .3398132
           _cons |    20.16242    1.799859     11.20    0.000      16.63476     23.69008
-----------------+----------------------------------------------------------------
 Variance         |
       e.fdferw3 |    684.7926    52.52119                    589.2164      795.872
         e.whpel |    863.5891    66.23426                    743.0584     1003.671
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.60, Prob > chi2 = 0.0058

. sem(avgcumdosew3->goferw3)(goferw3-> whpel) if gender==1, nocapslatent

Endogenous variables


Observed:  goferw3 whpel


Exogenous variables


Observed:  avgcumdosew3


Fitting target model:

Iteration 0:   log likelihood = -3887.3471
Iteration 1:   log likelihood = -3887.3471

Structural equation model                       Number of obs      =       340
 Estimation method = ml
 Log likelihood    = -3887.3471

-----------------+----------------------------------------------------------------
                 |                 OIM
                 |      Coef.    Std. Err.       z    P>|z|      [95% Con f. Interval]
-----------------+----------------------------------------------------------------
 Structural       |
   goferw3 <-     |
    avgcumdosew3 |     .095501    .3362642      0.28    0.776     -.5635648     .7545668
           _cons |    6.413035     .985593      6.51    0.000      4.481308     8.344762
  ---------------+----------------------------------------------------------------
   whpel <-       |
         goferw3 |    .2343573    .0974283      2.41    0.016      .0434013     .4253132
           _cons |    21.66037    1.731601     12.51    0.000       18.2665     25.05425
-----------------+----------------------------------------------------------------
 Variance         |
       e.goferw3 |    273.1843    20.95228                    235.0561     317.4972
         e.whpel |    881.8769    67.63687                    758.7938     1024.925
-----------------+----------------------------------------------------------------
LR test of model vs. saturated: chi2(1)   =      7.60, Prob > chi2 = 0.0058

.
.
. scalar W2maleELmed = "age radfmw3 sleep, illww3 and Hp2sxlife"

.
.
. ********************************************************************************
. * Male dose energy level trimmed regression summary
. *-------------------------------------------------------------------------------
.
.
. regress WHPel age educ2-educ7 marrw11-marrw13 marrw14 marrw15 ///
>      dvcew1 sepaw1 ///
>     shhlw1 shhousw1 phlthw1 suprtw1 fdferw1 healthef carcin  ///
>     dafter near chsize  bfmEL2 bfmEL4  avgcumdosew1 if gender==1, vce(cluster id)
note: marrw14 omitted because of collinearity

Linear regression                                      Number of obs =     338
                                                       F( 26,   337) =   28.75
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3999
                                                       Root MSE      =  24.235

(Std. Err. adjusted for 338 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .6183527    .1789293      3.46    0.001      .2663936     .9703117
       educ2 |    28.60858    13.59443      2.10    0.036      1.867955      55.3492
       educ3 |    24.51369    12.14821      2.02    0.044      .6178227     48.40956
       educ4 |    16.35072    12.80356      1.28    0.202     -8.834237     41.53568
       educ5 |     28.9029    12.71334      2.27    0.024      3.895399      53.9104
       educ6 |    27.30635    12.23922      2.23    0.026      3.231458     51.38125
       educ7 |    30.91241    16.01844      1.93    0.054     -.5963275     62.42114
     marrw11 |    8.252166    6.389701      1.29    0.197     -4.316556     20.82089
     marrw12 |   -21.77343    9.476595     -2.30    0.022     -40.41416    -3.132699
     marrw13 |   -2.683305    7.703491     -0.35    0.728     -17.83629     12.46968
     marrw14 |           0   (omitted)
     marrw15 |    23.10601    17.10609      1.35    0.178     -10.54214     56.75417
      dvcew1 |   -35.61387    15.50512     -2.30    0.022     -66.11288    -5.114865
      sepaw1 |     29.3133    15.12421      1.94    0.053     -.4364551     59.06305
      shhlw1 |   -.1236706    .0606364     -2.04    0.042     -.2429441    -.0043971
    shhousw1 |    .1308993    .0591896      2.21    0.028      .0144716      .247327
     phlthw1 |   -.2333923      .10458     -2.23    0.026      -.439104    -.0276806
     suprtw1 |    .0911964     .054574      1.67    0.096     -.0161523      .198545
     fdferw1 |    .0724489    .0502409      1.44    0.150     -.0263764     .1712741
    healthef |    .6050029     .144275      4.19    0.000      .3212099     .8887959
      carcin |   -.6773415    .1273417     -5.32    0.000     -.9278262    -.4268568
      dafter |    .0289208    .0096676      2.99    0.003      .0099044     .0479372
        near |   -.1587829    .0438246     -3.62    0.000     -.2449871    -.0725786
      chsize |   -.1405867    .0500458     -2.81    0.005     -.2390282    -.0421451
      bfmEL2 |   -1.161549    .5124324     -2.27    0.024     -2.169518    -.1535802
      bfmEL4 |   -.4526092    .1175493     -3.85    0.000     -.6838321    -.2213863
avgcumdosew1 |    .9479496    1.057609      0.90    0.371     -1.132397     3.028296
       _cons |    35384.23    9604.502      3.68    0.000       16491.9     54276.56
-------------+----------------------------------------------------------------

.     eststo wave1

.
.
. regress WHPel age educ2-educ7 marrw21-marrw23 marrw25 ///
>    radchw2 ///
>    havmil bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>     suprtw2  ///
>     near chsize  icdxcnt avgcumdosew2 if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 22,   339) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4045
                                                       Root MSE      =  23.973

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .2444639    .1509855      1.62    0.106     -.0525226     .5414503
       educ2 |    23.81448    14.42631      1.65    0.100     -4.561885     52.19084
       educ3 |    20.90318    13.88876      1.51    0.133      -6.41583     48.22219
       educ4 |    17.50249    14.43471      1.21    0.226      -10.8904     45.89537
       educ5 |    28.35315    14.32404      1.98    0.049       .177969     56.52834
       educ6 |    22.59929     14.0092      1.61    0.108     -4.956608      50.1552
       educ7 |    24.80169    17.20361      1.44    0.150     -9.037576     58.64096
     marrw21 |   -6.680446      7.4056     -0.90    0.368     -21.24716     7.886269
     marrw22 |   -9.226101    9.356658     -0.99    0.325     -27.63052     9.178319
     marrw23 |   -13.39345    6.897997     -1.94    0.053     -26.96171     .1748187
     marrw25 |   -15.85136    10.92161     -1.45    0.148     -37.33403     5.631305
     radchw2 |    .1171889    .0460525      2.54    0.011      .0266042     .2077737
      havmil |    .0276938    .0230684      1.20    0.231     -.0176815     .0730691
      bfmEL2 |   -1.658865    .5270993     -3.15    0.002     -2.695663    -.6220683
      bfmEL4 |   -.3829034    .1155964     -3.31    0.001       -.61028    -.1555268
     bfmEL16 |     .026152     .015568      1.68    0.094     -.0044701     .0567741
      carcin |   -.5961421    .0855537     -6.97    0.000     -.7644251     -.427859
    healthef |    .5173553    .1010253      5.12    0.000        .31864     .7160707
     suprtw2 |    .0674838     .035167      1.92    0.056     -.0016892     .1366568
        near |   -.1350195     .043128     -3.13    0.002     -.2198518    -.0501872
      chsize |   -.1400996    .0512046     -2.74    0.007     -.2408183    -.0393808
     icdxcnt |    3.037682     .987146      3.08    0.002      1.095979     4.979385
avgcumdosew2 |    .9919483    1.063382      0.93    0.352      -1.09971     3.083607
       _cons |    44177.84    9790.901      4.51    0.000      24919.27     63436.41
-------------+----------------------------------------------------------------

. eststo wave2

.
. regress WHPel age educ2-educ7  ///
>   emplw32-emplw34  radchw3 ///
>     bfmEL2 bfmEL4 bfmEL16 ///
>    carcin healthef ///
>    near chsize icdxcnt avgcumdosew3 if gender==1, vce(cluster id)

Linear regression                                      Number of obs =     340
                                                       F( 19,   339) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.3882
                                                       Root MSE      =  24.183

(Std. Err. adjusted for 340 clusters in id)
-------------+----------------------------------------------------------------
             |               Robust
        WHPel |      Coef.    Std. Err.       t    P>|t|      [95% Con f. Interval]
-------------+----------------------------------------------------------------
         age |    .0821968    .1405917      0.58    0.559     -.1943452     .3587387
       educ2 |    21.60517    12.68285      1.70    0.089     -3.341816     46.55216
       educ3 |    20.89634    11.80049      1.77    0.077     -2.315055     44.10774
       educ4 |    18.78453    12.48737      1.50    0.133     -5.777964     43.34701
       educ5 |    26.73457    12.07176      2.21    0.027      2.989569     50.47956
       educ6 |     23.6122    11.84095      1.99    0.047      .3212192     46.90319
       educ7 |    25.07642    15.59487      1.61    0.109     -5.598474     55.75132
     emplw32 |    5.835635    4.073836      1.43    0.153     -2.177546     13.84882
     emplw33 |     4.13417    4.756587      0.87    0.385     -5.221972     13.49031
     emplw34 |   -5.317768    4.593888     -1.16    0.248     -14.35388     3.718346
     radchw3 |     .107187    .0476161      2.25    0.025      .0135266     .2008473
      bfmEL2 |   -1.525516     .538026     -2.84    0.005     -2.583806    -.4672265
      bfmEL4 |   -.3830157    .1263966     -3.03    0.003     -.6316361    -.1343953
     bfmEL16 |    .0142534    .0068219      2.09    0.037      .0008348      .027672
      carcin |   -.5277715    .1127965     -4.68    0.000     -.7496406    -.3059024
    healthef |    .4494254    .1303576      3.45    0.001      .1930139     .7058369
        near |   -.1328695    .0431034     -3.08    0.002     -.2176534    -.0480857
      chsize |   -.1464739    .0515933     -2.84    0.005     -.2479572    -.0449905
     icdxcnt |    3.022184    .9862839      3.06    0.002      1.082177     4.962191
avgcumdosew3 |     1.00055    .9390882      1.07    0.287     -.8466242     2.847723
       _cons |    41521.57    9861.935      4.21    0.000      22123.28     60919.86
-------------+----------------------------------------------------------------

. eststo wave3

. estout  *,  cells(b(star fmt(%9.3f)) se(par)  p)                ///
>             stats(r2_a bic N, fmt(%9.3f %9.0g) labels(adjR^2 BIC))  ///
>             legend collabels(none) varlabels(_cons Constant)  ///
>             title("Trimmed Regression Models" ///
>             "of reconstructed dose on male energy level")

Trimmed Regression Models of reconstructed dose on male energy level
------------------------------------------------------------
                    wave1           wave2           wave3
------------------------------------------------------------
age                 0.618***        0.244           0.082
                  (0.179)         (0.151)         (0.141)
                    0.001           0.106           0.559
educ2              28.609*         23.814          21.605
                 (13.594)        (14.426)        (12.683)
                    0.036           0.100           0.089
educ3              24.514*         20.903          20.896
                 (12.148)        (13.889)        (11.800)
                    0.044           0.133           0.077
educ4              16.351          17.502          18.785
                 (12.804)        (14.435)        (12.487)
                    0.202           0.226           0.133
educ5              28.903*         28.353*         26.735*
                 (12.713)        (14.324)        (12.072)
                    0.024           0.049           0.027
educ6              27.306*         22.599          23.612*
                 (12.239)        (14.009)        (11.841)
                    0.026           0.108           0.047
educ7              30.912          24.802          25.076
                 (16.018)        (17.204)        (15.595)
                    0.054           0.150           0.109
marrw11             8.252
                  (6.390)
                    0.197
marrw12           -21.773*
                  (9.477)
                    0.022
marrw13            -2.683
                  (7.703)
                    0.728
o.marrw14           0.000
                      (.)
                        .
marrw15            23.106
                 (17.106)
                    0.178
dvcew1            -35.614*
                 (15.505)
                    0.022
sepaw1             29.313
                 (15.124)
                    0.053
shhlw1             -0.124*
                  (0.061)
                    0.042
shhousw1            0.131*
                  (0.059)
                    0.028
phlthw1            -0.233*
                  (0.105)
                    0.026
suprtw1             0.091
                  (0.055)
                    0.096
fdferw1             0.072
                  (0.050)
                    0.150
healthef            0.605***        0.517***        0.449***
                  (0.144)         (0.101)         (0.130)
                    0.000           0.000           0.001
carcin             -0.677***       -0.596***       -0.528***
                  (0.127)         (0.086)         (0.113)
                    0.000           0.000           0.000
dafter              0.029**
                  (0.010)
                    0.003
near               -0.159***       -0.135**        -0.133**
                  (0.044)         (0.043)         (0.043)
                    0.000           0.002           0.002
chsize             -0.141**        -0.140**        -0.146**
                  (0.050)         (0.051)         (0.052)
                    0.005           0.007           0.005
bfmEL2             -1.162*         -1.659**        -1.526**
                  (0.512)         (0.527)         (0.538)
                    0.024           0.002           0.005
bfmEL4             -0.453***       -0.383**        -0.383**
                  (0.118)         (0.116)         (0.126)
                    0.000           0.001           0.003
avgcumdosew1        0.948
                  (1.058)
                    0.371
marrw21                            -6.680
                                  (7.406)
                                    0.368
marrw22                            -9.226
                                  (9.357)
                                    0.325
marrw23                           -13.393
                                  (6.898)
                                    0.053
marrw25                           -15.851
                                 (10.922)
                                    0.148
radchw2                             0.117*
                                  (0.046)
                                    0.011
havmil                              0.028
                                  (0.023)
                                    0.231
bfmEL16                             0.026           0.014*
                                  (0.016)         (0.007)
                                    0.094           0.037
suprtw2                             0.067
                                  (0.035)
                                    0.056
icdxcnt                             3.038**         3.022**
                                  (0.987)         (0.986)
                                    0.002           0.002
avgcumdosew2                        0.992
                                  (1.063)
                                    0.352
emplw32                                             5.836
                                                  (4.074)
                                                    0.153
emplw33                                             4.134
                                                  (4.757)
                                                    0.385
emplw34                                            -5.318
                                                  (4.594)
                                                    0.248
radchw3                                             0.107*
                                                  (0.048)
                                                    0.025
avgcumdosew3                                        1.001
                                                  (0.939)
                                                    0.287
Constant        35384.229***    44177.838***    41521.571***
               (9604.502)      (9790.901)      (9861.935)
                    0.000           0.000           0.000
------------------------------------------------------------
adjR^2              0.350           0.361           0.350
BIC              3243.235        3240.196        3231.853
N                     338             340             340
------------------------------------------------------------
* p<0.05, ** p<0.01, *** p<0.001

.
.
. save chwide26june2012, replace
file chwide26june2012.dta saved