/* cd "C:\Users\chkim\OneDrive - The University of Kansas\Lectures\Soc910_AdvStat\examples" use soc910_1_data1.dta, clear * sample limitation keep if relate==1 | relate==2 keep if age>=25 & age<=54 gen married=marst==1 drop if (age_sp<25 | age_sp>54) & married==1 sort serial by serial: egen nadult = count(serial) keep if nadult==1 | nadult==2 keep if age>=35 & age<=44 save, replace */ cd "C:\Users\chkim\OneDrive - The University of Kansas\Lectures\Soc910_AdvStat\examples" use soc910_1_data1.dta, clear * Recode numlabel, add gen emp = 1 if empstat==1 replace emp = 0 if empstat==2 gen female=sex==2 gen single=marst==6 gen married = marst==1 gen races=5 replace races=1 if raced==100 & hispan==0 replace races=2 if raced==200 & hispan==0 replace races=4 if raced>=400 & raced<=679 & hispan==0 gen edu=1 replace edu=2 if educd==63 | educd==64 replace edu=3 if educd>=65 & educd<=100 replace edu=4 if educd==101 replace edu=5 if educd==114 replace edu=6 if educd==115 replace edu=7 if educd==116 replace edu=5 if edu>=5 gen age2=age*age gen immig=yrimmig!=0 * Logistic regression logit emp i.edu female age age2 [pw=perwt] logit emp i.edu female age age2 [pw=perwt], or logit, or margins margins, age margins, dydx(i.edu) margins, dydx(age) margins, at(age=40) logistic emp i.edu female age age2 [pw=perwt] reg emp i.edu female age age2 [pw=perwt]