Correlation Structures in Hierarchical Data Analysis Using PROC GLIMMIX vs. PROC GEE

[varatt90]

Hi all, 

I have a categorical variable with multiple unordered categories and am working with hierarchical data where clustering occurs at the hospital level. There is significant variance at the hospital level affecting my outcome, which is why I'm using PROC GLIMMIX instead of PROC GEE, as PROC GEE assumes an independent working correlation structure when you use a multinomial distribution.

My questions are:

1. Does the independent correlation structure in PROC GEE account for the nested data structure?
2. What correlation structure is assumed in PROC GLIMMIX, and does it adequately account for the nested data?

Here’s a sample of my code that I would like to run:

PROC GLIMMIX Data=Test Method=laplace;
CLASS hospitalid outcome (REF="0") year (REF="0") age (REF="0") sex (REF="0");
MODEL outcome = year age sex / DIST=multinomial LINK=glogit ALPHA=0.05 CL ODDSRATIO solution;
RANDOM Intercept / SUBJECT=hospitalid GROUP=outcome;
RUN;