. est clear
{\smallskip}
. title "Zero order tests"
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{\smallskip}
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*****                                                                     *****
*****                                                                     *****
*****                          Zero order tests                           *****
*****                                                                     *****
*****                                                                     *****
*****                                             1 Jul 2012    13:58:04  *****
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{\smallskip}
. set more off
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. foreach var in HP2work HP2hmcare HP2probsoc HP2pbfhm HP2sxlife HP2inthob ///
>       HP2vacatn  {\lbr}
  2.       forvalues k=2/2 {\lbr} 
  3.   logit `var' avgcumdosew2 if gender==`k', nolog
  4.   eststo w2`var'dose
  5.   {\rbr}
  6.  {\rbr}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =       6.63
                                                  Prob > chi2     =     0.0100
Log likelihood = -203.24758                       Pseudo R2       =     0.0160
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
     HP2work {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .2046594   .0826501     2.48   0.013     .0426681    .3666507
       _cons {\VBAR}  -1.260388   .1448325    -8.70   0.000    -1.544255   -.9765218
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =       0.01
                                                  Prob > chi2     =     0.9082
Log likelihood = -233.72194                       Pseudo R2       =     0.0000
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
   HP2hmcare {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}  -.0093108   .0810645    -0.11   0.909    -.1681944    .1495727
       _cons {\VBAR}  -.6356448     .13193    -4.82   0.000    -.8942228   -.3770668
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =      25.69
                                                  Prob > chi2     =     0.0000
Log likelihood = -170.72516                       Pseudo R2       =     0.0700
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
  HP2probsoc {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .5024747   .1391198     3.61   0.000      .229805    .7751444
       _cons {\VBAR}  -1.841993   .1807682   -10.19   0.000    -2.196292   -1.487694
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =       1.97
                                                  Prob > chi2     =     0.1602
Log likelihood = -138.91068                       Pseudo R2       =     0.0070
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
    HP2pbfhm {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .1290516   .0853896     1.51   0.131    -.0383089    .2964121
       _cons {\VBAR}   -2.03386   .1824844   -11.15   0.000    -2.391523   -1.676197
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =      13.99
                                                  Prob > chi2     =     0.0002
Log likelihood = -200.62862                       Pseudo R2       =     0.0337
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
   HP2sxlife {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .3220323   .1022608     3.15   0.002     .1216048    .5224598
       _cons {\VBAR}  -1.353229   .1520692    -8.90   0.000     -1.65128   -1.055179
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =       5.33
                                                  Prob > chi2     =     0.0210
Log likelihood = -169.44834                       Pseudo R2       =     0.0155
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\HLI{13}{\TOPT}\HLI{64}
   HP2inthob {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .1881347   .0796521     2.36   0.018     .0320195      .34425
       _cons {\VBAR}  -1.691176   .1610367   -10.50   0.000    -2.006802    -1.37555
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
Logistic regression                               Number of obs   =        363
                                                  LR chi2(1)      =       4.26
                                                  Prob > chi2     =     0.0389
Log likelihood = -165.38435                       Pseudo R2       =     0.0127
{\smallskip}
\HLI{13}{\TOPT}\HLI{64}
   HP2vacatn {\VBAR}      Coef.   Std. Err.      z    P>|z|     [95\% Conf. Interval]
\HLI{13}{\PLUS}\HLI{64}
avgcumdosew2 {\VBAR}   .1706012   .0795148     2.15   0.032     .0147551    .3264474
       _cons {\VBAR}  -1.730143   .1632828   -10.60   0.000    -2.050172   -1.410115
\HLI{13}{\BOTT}\HLI{64}
{\smallskip}
. 
.  
. *------- estout code snippt
. 
. estout  *,      cells(b(star fmt(\%9.3f)) se(par) t p)                ///
>                 stats( bic N, fmt(\%9.3f \%9.0g) )        ///
>                 legend collabels(none) varlabels(_cons Constant)  ///
>                 mlabels(workw2  homecarew2 socprobsw2 pbfhmw2 sexlifew2 intho
> bw2 vactnw2) ///
>                                 title("Zero-order regression coefficients" //
> /
>                  "of reconstructed dose for females in wave 2")
{\smallskip}
Zero-order regression coefficients of reconstructed dose for females in wave 2
\HLI{79}
\HLI{45}
                   workw2      homecarew2      socprobsw2         pbfhmw2      
>  sexlifew2        inthobw2         vactnw2   
\HLI{79}
\HLI{45}
main                                                                           
>                                              
avgcumdosew2        0.205*         -0.009           0.502***        0.129      
>      0.322**         0.188*          0.171*  
                  (0.083)         (0.081)         (0.139)         (0.085)      
>    (0.102)         (0.080)         (0.080)   
                    2.476          -0.115           3.612           1.511      
>      3.149           2.362           2.146   
                    0.013           0.909           0.000           0.131      
>      0.002           0.018           0.032   
Constant           -1.260***       -0.636***       -1.842***       -2.034***   
>     -1.353***       -1.691***       -1.730***
                  (0.145)         (0.132)         (0.181)         (0.182)      
>    (0.152)         (0.161)         (0.163)   
                   -8.702          -4.818         -10.190         -11.145      
>     -8.899         -10.502         -10.596   
                    0.000           0.000           0.000           0.000      
>      0.000           0.000           0.000   
\HLI{79}
\HLI{45}
bic               418.284         479.233         353.239         289.610      
>    413.046         350.685         342.558   
N                     363             363             363             363      
>        363             363             363   
\HLI{79}
\HLI{45}
* p<0.05, ** p<0.01, *** p<0.001
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.                 
