Chapter 11, Section 11.4

Muscatine Coronary Risk Factor Study

Marginal Logistic Regression Model

data obesity;
     infile 'muscatine.dat';
     input id gender baseage age occasion y;

cage=age - 12;
cage2=cage*cage;

title1 Marginal Logistic Regression Model for Obesity;
title2 Muscatine Coronary Risk Factor Study;

proc genmod descending;
     class id occasion;
     model y=gender cage cage2 gender*cage gender*cage2 / dist=bin link=logit
     type3 wald;
     contrast 'Age X Gender Interaction' gender*cage 1, gender*cage2 1 /wald;
     repeated subject=id / withinsubject=occasion logor=fullclust;
run;

proc genmod descending;
     class id occasion;
     model y=gender cage cage2 / dist=bin link=logit
     type3 wald;
     repeated subject=id / withinsubject=occasion logor=fullclust;
run;

proc genmod descending;
     class id occasion;
     model y=gender cage cage2 / dist=bin link=logit
     type3 wald;
     repeated subject=id / withinsubject=occasion
         logor=zrep( (1 2) 1 0,
                           (1 3) 0 1,
                           (2 3) 1 0);
run;

<Selected Output>

Clinical Trial of Antibiotics for Leprosy

Marginal Log-linear Regression Model

data leprosy;
     infile 'leprosy.dat';
     input drug $ y1 y2;
id+1;

A=0;
B=0;
Antibiotic=0;

if drug='A' then A=1;
if drug='B' then B=1;
Antibiotic=A+B;

data leprosy;
     set leprosy;
     y=y1; time=0; output;
     y=y2; time=1; output;

title1 Marginal Log-linear Regression Model for Leprosy Bacilli;
title2 Clinical Trial of Antibiotics for Leprosy;

proc genmod;
     class id;
     model y= time A*time B*time / d=poisson link=log type3 wald;
     contrast 'Drug x Time Interaction' A*time 1, B*time 1 / wald;
     repeated subject=id / modelse type=un corrw;
run;

<Selected Output>

proc genmod;
     class id ;
     model y= time Antibiotic*time / d=poisson link=log type3 wald;
     repeated subject=id / modelse type=un corrw;
run;

<Selected Output>