*1.1 BINARY LOGIT

logit labour retnat class union swreg urbrur1 lrself

dis exp(0.466)

logit labour retnat class union swreg urbrur1 lrself, or
logistic labour retnat class union swreg urbrur1 lrself


*1.2 PREDICTIONS: INDIVIDUAL AND IDEAL

logit labour retnat class union swreg urbrur1 lrself

prvalue, rest(median)

prvalue, x(retnat 1 lrself 10 class 3 union 0 urbrur1 1 swreg 0)

prchange, rest(median)

prgen lrself, gen(lrs) rest(median) ci
twoway (line lrsp1 lrsx, lcolor(black)) (line lrsp1lb lrsx, color(black) lpattern(dash))(line lrsp1ub lrsx, lcolor(black) lpattern(dash)), xscale(range(1 10.)) legend(order(1 "Pr(Y=1|x)" 2 "95% CI"))


*EXERCISE

codebook votelab2001

logit labour retnat class union swreg urbrur1 lrself votelab2001

prvalue, x(votelab2001 0) rest(median)
prvalue, x(votelab2001 1) rest(median)


*1.3 BINARY PROBIT

probit labour retnat class union swreg urbrur1 lrself


*1.4 MODEL FIT AND SELECTION

*Constrained model ('if' command used to ensure the same cases are included in both models):
logit labour if retnat<.&class<.&union<.&swreg<.&urbrur1<.&lrself<.
*Unconstrained model:
logit labour retnat class union swreg urbrur1 lrself

dis chi2tail( 6, 75.588)

test class union

test class = union

logit labour retnat union swreg urbrur1 lrself 
logit labour retnat class swreg urbrur1 lrself if e(sample)
gen tempsamp = 1 if e(sample)
logit labour retnat union swreg urbrur1 lrself if tempsamp == 1
fitstat, saving(mod1)
logit labour retnat class swreg urbrur1 lrself if tempsamp == 1
fitstat, using(mod1)