Determining if Random Effects are Significant in Proc Glimmix

[ksn999]

Hi all,

I am used to working in proc mixed and using the option covtest in the first line to get Z and p-values of covariance parameter estimates (because I have a random effect that I only leave in if it is significant). For one of my variables, I had to move to proc glimmix because I needed to do a median split on the data and assess it using a binary distribution model. However, I can't seem to figure out how to get the same Z and p-value outputs for the covariance parameter estimates table. Is there a way to do that? I've read the literature on covtest in glimmix, but none of the options give output on individual random effects (only all random effects as a whole). This is the sas code I am using currently:

proc glimmix data=BL_SRms ;
class condition time Subject_ID;
model il6Median_Split(event='1')=condition time condition*time / dist=binary;
random Subject_ID Condition(Subject_ID);
random condition / subject=Subject_ID*time residual;
covtest diagg;
run;

What I want is something like this:

Right now, proc Glimmix is only giving me a table with the estimate and standard error. I want the z value and p-test too.

Other information that may or may not be relevant: I am using SAS University Edition.

[StatsMan]

The WALD option on the COVTEST statement might do what you want.  Try

   covtest / wald;

That will match the results you would see from MIXED (using COVTEST option) if your model had normal errors.