02-10-2014 08:32 AM
I have some basic questions regarding PROC GLIMMIX and PROC MIXED, and probably other mixed models related PROC's.
Assume that I have an outcome variable Y, continuous, and a treatment variable X with 2 levels. Let's also say that every subject in the analysis contributes 3 data points (can be 3 treatments in one person, or students within schools).
If I write this code:
proc mixed data = ....;
model Y = X / solution cl;
what is the difference between:
random intercept / subject = SubjID;
and let's say (if it's a legal statement):
random Treatment / subject = SubjID;
I tried it on a small data set and the first two options gave me identical results. This question of course is relevant also for glimmix with a dist = binary.
And one more question, if I have this scenario, and I run a PROC MIXED once with random statement and once with REPEATED, and the results are very similar and leading to the same conclusions, how can I choose if to use R side or G side covariance ?
Thank you !
02-14-2014 02:14 PM
A really valuable source is SAS for Mixed Models, 2nd ed. by Littell et al. I can't imagine working with SAS and mixed models without having this available.
And it will answer every one of your questions that you posed.