There is a random intercept per "site" not per subject. The "fulldata" data set contains the data to which I want to fit the model, and an appended data set of new patients, which are patients with the same "var1","var2","var3" values but one for each site and their outcome variable is missing. From this code, I can obtain predicted probabilities for this same patient as if they had been treated at each site. This code also outputs a standard error and a 95% CI. In general, I want to know what the interpretation of the standard error and the 95% CI for this prediction are, and if based on the documentation these should not be used for a new patient that was not in the original data set. Proc glimmix data=fulldata;
class site var1 var2 var3;
model outcome(event='1')=var1 var2 var3 /link=logit dist=binary;
random intercept/subject = site;
output out=predOut predicted(blup ilink)=predProbs stderr(blup ilink)=stderr lcl(blup ilink)=lower ucl(blup ilink)=upper;
run;
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