Fixed Effects Regression Methods for Longitudinal Data Using SAS

3.5. Subject-Specific versus Population-Averaged Coefficients

In chapter 2, we saw that estimates for the linear random effects model could also be obtained by using GEE estimation in PROC GENMOD. Although GEE estimation also works well for logistic regression models, the results are not equivalent to the random effects estimates produced by PROC NLMIXED. Let's first examine the differences for our NLSY example, and then we'll discuss the nature of those differences. Here's a GENMOD program for a model that's similar to the one we just estimated in NLMIXED:

PROC GENMOD DATA=teenyrs5;
   CLASS year id;
   MODEL pov = year mother spouse inschool hours
         / DIST=BINOMIAL;
   REPEATED SUBJECT=id / TYPE=EXCH MODELSE;
RUN;

The DIST=BINOMIAL option specifies a ...