Dear all, I have a set of evaluation scores (from 1=worst quality to 5=best quality) given by N=25 subjects to each of M=90 videos varying by content, resolution and compression. The contents are six video games and the subjects are individuals of similar age and playing experience. The main interest is in the fixed effects of resolution and compression with respect to the population of games and individuals. Thus I would like to perform a GEE marginal analysis with 1-nested log odds ratios, but I understand that is not available for the multinomial. I ended up using the following repeated statement repeated subject=Subject* Game / logor=EXCH; which is not what I was looking for but probably gives similar answer. The full code is proc gee data=scores; class Subject Game Resolution; model Score = Game Resolution Game*Resolution sqrtComp logComp logComp*Game logComp*Resolution/ dist=mult type3; repeated subject=subject*Game/logor=Exch; output out=out(keep= config Game Resolution Compression Pred) Predicted=Pred; ods output GEEFitCriteria=QIC2; run; Is there any other way? Would glimmix with method=Laplace helping in any way? Thank you Sergio Pezzulli
... View more