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smrose · ‎04-11-2018

So after thinking about it some more I realized the repeated statement did not make sense in the context because my outcome was not repeated. That meant to specify my subgroups I needed to use the random statement. The only thing that could randomly varies in the model are the level 1 observations. So I ended up fitting a model like this: proc mixed data = dataset noclprint namelen=32 covtest plots = all ; class subjectid ; model SSPG = shannonc /solution ddfm = bw cl ; random shannonc /subject = subjectid; run; the degrees of freedom were reasonable.

smrose · ‎04-08-2018

I'm trying to model a group level attribute that is only measured once during study using individual level predictor that was measured anywhere from 1 to 111 times/per person with 660 observations and 60 people. How do I specify that my outcome is a group level attribute that has only been measured once per subject? I think with code my outcome is being analyzed as if it were dis-aggregated across all time points. proc mixed data = analysis.labshmp9 noclprint empirical ; class subjectid ; model sspg = shannon | shannon /solution ; repeated / subject = subjectid ; run;

smrose · ‎01-23-2018

Did you ever find a solution to this problem?

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Date Last Visited	‎04-25-2018 02:48 PM

Re: Proc Mixed with Group Level outcome

Proc Mixed with Group Level outcome

Re: Output constraint parameter from PROC GLMSELECT?

Does proc glmselect support random effects

Increase variable name length from 32 to 128 characters

Metadata: More space please

Re: Proc Mixed with Group Level outcome

Proc Mixed with Group Level outcome

Re: Output constraint parameter from PROC GLMSELECT?