. set more off
{\smallskip}
. cd /Users/robertyaffee/Documents/data/research/chwk/phase3/data/panel
/Users/robertyaffee/Documents/data/research/chwk/phase3/data/panel
{\smallskip}
. use ch3wMaster27mar2012, clear
{\smallskip}
. 
. *****  Assessing within subjects effects *******
. 
. 
. anova radhlw ranown id  wave if gender==1, repeated(id wave) 
{\smallskip}
                           Number of obs =    1020     R-squared     =  0.9070
                           Root MSE      = 13.4841     Adj R-squared =  0.8602
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1202064.85   341  3525.11688      19.39     0.0000
                         {\VBAR}
                  ranown {\VBAR}  102458.824    33  3104.81283      17.08     0.0000
                      id {\VBAR}  1032408.78   306  3373.88491      18.56     0.0000
                    wave {\VBAR}  494.752941     2  247.376471       1.36     0.2572
                         {\VBAR}
                Residual {\VBAR}   123274.58   678  181.820915   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1325339.44  1019  1300.62751   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  34        (33 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0033
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    306    18.56   0.0000     .        .      0.0414
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2     1.36   0.2572     .        .      0.2443
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1020
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   45.69412   .7312779    62.49   0.000     44.26084     47.1274
          2  {\VBAR}   46.80588   .7312779    64.01   0.000      45.3726    48.23916
          3  {\VBAR}   47.37059   .7312779    64.78   0.000     45.93731    48.80387
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% of own health affected")  title("\% own health affected
> " "by Chornobyl radiation") ///
>   subtitle(male respondents) graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
. contrast r.wave
{\smallskip}
Contrasts of marginal linear predictions
{\smallskip}
Margins      : asbalanced
{\smallskip}
\HLI{13}{\TOPT}\HLI{34}
             {\VBAR}         df           F        P>F
\HLI{13}{\PLUS}\HLI{34}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}          1        1.16     0.2827
   (3 vs 1)  {\VBAR}          1        2.63     0.1055
      Joint  {\VBAR}          2        1.36     0.2572
             {\VBAR}
    Residual {\VBAR}        678
\HLI{13}{\BOTT}\HLI{34}
{\smallskip}
\HLI{13}{\TOPT}\HLI{48}
             {\VBAR}   Contrast   Std. Err.     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{48}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}   1.111765   1.034183     -.9188219    3.142351
   (3 vs 1)  {\VBAR}   1.676471   1.034183      -.354116    3.707057
\HLI{13}{\BOTT}\HLI{48}
{\smallskip}
. gr save rhlmmeans.gph, replace
(file rhlmmeans.gph saved)
{\smallskip}
.  
.     
. anova radhlw  ranown id wave if gender==2, repeated(id wave) 
{\smallskip}
                           Number of obs =    1088     R-squared     =  0.8466
                           Root MSE      = 16.9776     Adj R-squared =  0.7694
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1150066.39   364  3159.52305      10.96     0.0000
                         {\VBAR}
                  ranown {\VBAR}   143990.58    45  3199.79066      11.10     0.0000
                      id {\VBAR}  885260.749   317  2792.62066       9.69     0.0000
                    wave {\VBAR}   3901.0143     2  1950.50715       6.77     0.0012
                         {\VBAR}
                Residual {\VBAR}  208396.986   723  288.239261   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1358463.37  1087  1249.73631   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  46        (45 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0032
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    317     9.69   0.0000     .        .      0.0757
                Residual {\VBAR}    723
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2     6.77   0.0012     .        .      0.0097
                Residual {\VBAR}    723
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1088
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   56.72376   .8923234    63.57   0.000     54.97484    58.47268
          2  {\VBAR}   59.90909   .8910935    67.23   0.000     58.16258     61.6556
          3  {\VBAR}   61.01377   .8910935    68.47   0.000     59.26726    62.76029
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% own health affected" )  ///
>   title("\% of own health affected" "by Chornobyl radiation") subtitle(female 
> respondents) ///
>   graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   
. 
. gr save rhlfmeans.gph, replace
(file rhlfmeans.gph saved)
{\smallskip}
.  contrast r.wave
{\smallskip}
Contrasts of marginal linear predictions
{\smallskip}
Margins      : asbalanced
{\smallskip}
\HLI{13}{\TOPT}\HLI{34}
             {\VBAR}         df           F        P>F
\HLI{13}{\PLUS}\HLI{34}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}          1        7.06     0.0080
   (3 vs 1)  {\VBAR}          1       12.48     0.0004
      Joint  {\VBAR}          2        6.77     0.0012
             {\VBAR}
    Residual {\VBAR}        723
\HLI{13}{\BOTT}\HLI{34}
{\smallskip}
\HLI{13}{\TOPT}\HLI{48}
             {\VBAR}   Contrast   Std. Err.     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{48}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}   3.352355   1.261501      .8757116    5.828998
   (3 vs 1)  {\VBAR}   4.457038   1.261501      1.980395    6.933681
\HLI{13}{\BOTT}\HLI{48}
{\smallskip}
.   
.   
.   gr box radhlw, over(gender) over(wave)
{\smallskip}
. 
. gr combine rhlmmeans.gph rhlfmeans.gph, col(2) title(Self-reported Chornobyl 
> health risk)
{\smallskip}
. gr save crhlmeans.gph, replace
(file crhlmeans.gph saved)
{\smallskip}
. gr export crhlmeans.eps, replace 
(file crhlmeans.eps written in EPS format)
{\smallskip}
. 
. gr twoway qfitci radhlw wave, by(gender) xlabel(1 2 3) title(qfit plot of Rad
> hlw by wave )  ///
>   ytitle("\% of own health affected" "by Chornobyl radiation")
{\smallskip}
.   
. 
. 
. 
. 
. anova radfmw ranown id  wave if gender==1, repeated(id wave) 
{\smallskip}
                           Number of obs =    1020     R-squared     =  0.8385
                           Root MSE      = 17.2438     Adj R-squared =  0.7572
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1046471.34   341  3068.83091      10.32     0.0000
                         {\VBAR}
                  ranown {\VBAR}  88757.8431    33  2689.63161       9.05     0.0000
                      id {\VBAR}  905994.963   306  2960.76785       9.96     0.0000
                    wave {\VBAR}  6922.23725     2  3461.11863      11.64     0.0000
                         {\VBAR}
                Residual {\VBAR}  201601.763   678  297.347733   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}   1248073.1  1019  1224.80187   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  34        (33 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0033
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    306     9.96   0.0000     .        .      0.0766
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2    11.64   0.0000     .        .      0.0007
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1020
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   50.88235   .9351749    54.41   0.000     49.04944    52.71526
          2  {\VBAR}   56.01471   .9351749    59.90   0.000      54.1818    57.84762
          3  {\VBAR}   56.73235   .9351749    60.66   0.000     54.89944    58.56526
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% family health affected" "by Chornobyl radiation")  ///
>   title("Percent of family health affected" "by Chornobyl radiation")  subti(
> male reports) ///
>   graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
. 
.   
. contrast r.wave
{\smallskip}
Contrasts of marginal linear predictions
{\smallskip}
Margins      : asbalanced
{\smallskip}
\HLI{13}{\TOPT}\HLI{34}
             {\VBAR}         df           F        P>F
\HLI{13}{\PLUS}\HLI{34}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}          1       15.06     0.0001
   (3 vs 1)  {\VBAR}          1       19.57     0.0000
      Joint  {\VBAR}          2       11.64     0.0000
             {\VBAR}
    Residual {\VBAR}        678
\HLI{13}{\BOTT}\HLI{34}
{\smallskip}
\HLI{13}{\TOPT}\HLI{48}
             {\VBAR}   Contrast   Std. Err.     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{48}
        wave {\VBAR}
   (2 vs 1)  {\VBAR}   5.132353   1.322537      2.535592    7.729114
   (3 vs 1)  {\VBAR}       5.85   1.322537      3.253239    8.446761
\HLI{13}{\BOTT}\HLI{48}
{\smallskip}
. gr save rfmwmmeans.gph, replace    
(file rfmwmmeans.gph saved)
{\smallskip}
. anova radfmw  ranown id wave if gender==2, repeated(id wave) 
{\smallskip}
                           Number of obs =    1089     R-squared     =  0.7540
                           Root MSE      =  20.937     Adj R-squared =  0.6303
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  972807.739   364  2672.54873       6.10     0.0000
                         {\VBAR}
                  ranown {\VBAR}  101740.326    45  2260.89614       5.16     0.0000
                      id {\VBAR}  790034.137   317  2492.22125       5.69     0.0000
                    wave {\VBAR}  16260.1947     2  8130.09734      18.55     0.0000
                         {\VBAR}
                Residual {\VBAR}  317372.472   724  438.359768   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1290180.21  1088   1185.8274   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  46        (45 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0032
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    317     5.69   0.0000     .        .      0.1242
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2    18.55   0.0000     .        .      0.0000
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1089
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}    60.0551    1.09891    54.65   0.000     57.90127    62.20892
          2  {\VBAR}   67.89532    1.09891    61.78   0.000     65.74149    70.04914
          3  {\VBAR}   68.56749    1.09891    62.40   0.000     66.41367    70.72132
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% of family health affected" "by Chornobyl radiation") /
> //
>   title("Percent of family health affected" "by Chornobyl radiation") ///
>   graphregion(color(sand)) subtitle(female reports) 
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   
.   
. gr save rfmwfmeans.gph, replace
(file rfmwfmeans.gph saved)
{\smallskip}
. 
. gr combine rfmwfmeans.gph rfmwmmeans.gph, col(2) title(Self-reported Chornoby
> l related family health risk)
{\smallskip}
. gr save cfmwmeans.gph, replace
(file cfmwmeans.gph saved)
{\smallskip}
. gr export cfmwmeans.eps, replace    
(file cfmwmeans.eps written in EPS format)
{\smallskip}
. 
. 
. 
. anova radltw ranown id  wave if gender==1, repeated(id wave) 
{\smallskip}
                           Number of obs =    1019     R-squared     =  0.8766
                           Root MSE      = 15.2647     Adj R-squared =  0.8145
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1120813.17   341  3286.84214      14.11     0.0000
                         {\VBAR}
                  ranown {\VBAR}  108102.206    33  3275.82442      14.06     0.0000
                      id {\VBAR}  927531.074   306   3031.1473      13.01     0.0000
                    wave {\VBAR}  859.868837     2  429.934419       1.85     0.1588
                         {\VBAR}
                Residual {\VBAR}  157749.464   677  233.012503   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1278562.64  1018  1255.95544   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  34        (33 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0033
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    306    13.01   0.0000     .        .      0.0593
                Residual {\VBAR}    677
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2     1.85   0.1588     .        .      0.1753
                Residual {\VBAR}    677
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1019
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   53.52507   .8290673    64.56   0.000     51.90013    55.15002
          2  {\VBAR}   51.95294   .8278471    62.76   0.000     50.33039    53.57549
          3  {\VBAR}   51.29706   .8278471    61.96   0.000     49.67451    52.91961
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% health affected by" "cumulative lifetime exposure to r
> adiation") ///
>   title("\% health affected by" "lifetime exposure to radiation" ) ///
>   subtitle("male respondents") graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   gr save rltmmeans.gph, replace
(file rltmmeans.gph saved)
{\smallskip}
.   gr export rltmmeans.eps, replace
(file rltmmeans.eps written in EPS format)
{\smallskip}
.   
.     
. anova radltw  ranown id wave if gender==2, repeated(id wave) 
{\smallskip}
                           Number of obs =    1089     R-squared     =  0.8680
                           Root MSE      = 16.0499     Adj R-squared =  0.8017
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1226549.04   364  3369.64022      13.08     0.0000
                         {\VBAR}
                  ranown {\VBAR}   124073.08    45  2757.17955      10.70     0.0000
                      id {\VBAR}  996650.643   317  3144.00834      12.21     0.0000
                    wave {\VBAR}  1913.55556     2  956.777778       3.71     0.0248
                         {\VBAR}
                Residual {\VBAR}  186501.111   724   257.59822   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1413050.15  1088  1298.75933   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  46        (45 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0032
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    317    12.21   0.0000     .        .      0.0602
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2     3.71   0.0248     .        .      0.0547
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1089
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   62.01928   .8423995    73.62   0.000     60.36821    63.67036
          2  {\VBAR}    64.1708   .8423995    76.18   0.000     62.51973    65.82187
          3  {\VBAR}    65.2011   .8423995    77.40   0.000     63.55003    66.85217
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% health affected by" "cumulative lifetime exposure to r
> adiation") ///
>   title("\% health affected by" "lifetime exposure to radiation" ) ///
>   subtitle("female respondents") graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   gr save rltfmeans.gph, replace
(file rltfmeans.gph saved)
{\smallskip}
.   gr export rltfmeans.eps, replace
(file rltfmeans.eps written in EPS format)
{\smallskip}
.   
. gr combine rltmmeans.gph rltfmeans.gph, col(2) title(Self-reported lifetime r
> adiation health risk)
{\smallskip}
. gr export  crltmeans.eps, replace  
(file crltmeans.eps written in EPS format)
{\smallskip}
.     
.     
. anova radchw ranown id  wave if gender==1, repeated(id wave) 
{\smallskip}
                           Number of obs =    1020     R-squared     =  0.8260
                           Root MSE      = 17.6892     Adj R-squared =  0.7385
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1007051.14   341  2953.22914       9.44     0.0000
                         {\VBAR}
                  ranown {\VBAR}  84725.4902    33   2567.4391       8.21     0.0000
                      id {\VBAR}  860813.243   306  2813.11517       8.99     0.0000
                    wave {\VBAR}  8808.92353     2  4404.46176      14.08     0.0000
                         {\VBAR}
                Residual {\VBAR}  212151.076   678  312.907192   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1219202.21  1019   1196.4693   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  34        (33 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0033
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    306     8.99   0.0000     .        .      0.0844
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2    14.08   0.0000     .        .      0.0002
                Residual {\VBAR}    678
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1020
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   53.09118   .9593306    55.34   0.000     51.21092    54.97143
          2  {\VBAR}   48.68235   .9593306    50.75   0.000      46.8021    50.56261
          3  {\VBAR}   45.95882   .9593306    47.91   0.000     44.07857    47.83908
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% pollution from Chornobyl") ///
>   title("\% pollution from Chornobyl" ) ///
>   subtitle("male respondents") graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   gr save rdchmmeans.gph, replace
(file rdchmmeans.gph saved)
{\smallskip}
. 
.   
.     
. anova radchw  ranown id wave if gender==2, repeated(id wave) 
{\smallskip}
                           Number of obs =    1089     R-squared     =  0.8266
                           Root MSE      = 18.0018     Adj R-squared =  0.7395
{\smallskip}
                  Source {\VBAR}  Partial SS    df       MS           F     Prob > F
              \HLI{11}{\PLUS}\HLI{52}
                   Model {\VBAR}  1118621.06   364  3073.13479       9.48     0.0000
                         {\VBAR}
                  ranown {\VBAR}  121557.826    45  2701.28502       8.34     0.0000
                      id {\VBAR}  917114.363   317  2893.10525       8.93     0.0000
                    wave {\VBAR}  289.239669     2  144.619835       0.45     0.6402
                         {\VBAR}
                Residual {\VBAR}  234622.094   724  324.063665   
              \HLI{11}{\PLUS}\HLI{52}
                   Total {\VBAR}  1353243.16  1088  1243.78967   
{\smallskip}
{\smallskip}
Between-subjects error term:  ranown
                     Levels:  46        (45 df)
     Lowest b.s.e. variable:  ranown
{\smallskip}
Repeated variable: id
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.0032
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                      id {\VBAR}    317     8.93   0.0000     .        .      0.0818
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
Repeated variable: wave
                                          Huynh-Feldt epsilon        =    .
                                          Greenhouse-Geisser epsilon =    .
                                          Box's conservative epsilon =  0.5000
{\smallskip}
                                            \HLI{12} Prob > F \HLI{12}
                  Source {\VBAR}     df      F    Regular    H-F      G-G      Box
              \HLI{11}{\PLUS}\HLI{52}
                    wave {\VBAR}      2     0.45   0.6402     .        .      0.5045
                Residual {\VBAR}    724
              \HLI{11}{\BOTT}\HLI{52}
{\smallskip}
. margins, within(wave)
{\smallskip}
Predictive margins                                Number of obs   =       1089
{\smallskip}
Expression   : Linear prediction, predict()
within       : wave
Empty cells  : reweight
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
             {\VBAR}            Delta-method
             {\VBAR}     Margin   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
        wave {\VBAR}
          1  {\VBAR}   61.39669   .9448478    64.98   0.000     59.54483    63.24856
          2  {\VBAR}   62.52893   .9448478    66.18   0.000     60.67706    64.38079
          3  {\VBAR}   61.47934   .9448478    65.07   0.000     59.62747    63.33121
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. marginsplot, ytitle("\% pollution from Chornobyl") ///
>   title("\% pollution from Chornobyl" ) ///
>   subtitle("female respondents") graphregion(color(sand))
{\smallskip}
  Variables that uniquely identify margins: wave
{\smallskip}
.   gr save rdchfmeans.gph, replace
(file rdchfmeans.gph saved)
{\smallskip}
. 
.   
. gr combine rdchmmeans.gph rdchfmeans.gph, col(2) title(\% of pollution due to 
> Chornobyl)
{\smallskip}
. gr export  crdchmeans.eps, replace  
(file crdchmeans.eps written in EPS format)
{\smallskip}
.     
.     
.     
.     
.  sjlog close, replace   
{\smallskip}
