* set end of line marker;
# delimit;
set more off;
* increase memory;
set memory 20m;
* write results to file;
log using c:\bill\jpsm\nlms_data.log,replace;
* load up sas data set;
use c:\bill\jpsm\nlms_data;
* get contents of data file;
desc;
* get summary statistics;
sum;
* define the duration data in the analysis;
stset followh, failure(deathh) id(hhid);
* graph the kaplan-meier functions;
* output the graphs to a file;
sts graph;
graph save c:\bill\jpsm\nlms_graph1.gph, replace;
* graph the hazards;
sts graph, hazard;
graph save c:\bill\jpsm\nlms_graph2.gph, replace;
* you can draw graphs for various subgroups;
* output the graphs to a file;
sts graph, by(educ);
graph save c:\bill\jpsm\nlms_graph3.gph, replace;
* graph the hazards;
* output the graphs to a file;
sts graph, hazard by(educ);
graph save c:\bill\jpsm\nlms_graph4.gph, replace;
* run a duration model where the hazard varies across;
* people. first, ask stata to print out the raw;
* coefficients (nohr option), then do default;
* show weibull first, then exponential;
* first, construct dummies for the income and;
* education categories. in the regression statement;
* _Ie star include all variables beginning with _Ie;
* and _Ii star includes all variables starting with;
* _Ii;
xi i.income i.educ;
streg age raceh1 raceh2 _Ie* _Ii*, d(weibull) nohr;
* now get the hazard ratios where all coefs are raised to;
* exp(b1);
streg age raceh1 raceh2 _Ie* _Ii*, d(weibull);
* for compairson purposes, look at results from an exponential;
streg age raceh1 raceh2 _Ie* _Ii*, d(exp) nohr;
streg age raceh1 raceh2 _Ie* _Ii*, d(exp);
* estimate cox proportional hazards model;
stcox age raceh1 raceh2 _Ie* _Ii*;
stsplit bereavement, after(time=followw) at(0);
recode bereavement -1=0 0=1;
stcox age raceh1 raceh2 _Ie* _Ii* bereavement;
log close;
log close;