Hello! I would like some help on my modeling for the following situation. I have a dataset with 200 subjects. For each subject (indicated by ID), their situation is determined at three moments, being either 'living at home', 'institutionalized', or 'dead' (situation is my dependent outcome). At the first measurement moment, every subject lives at home. I want to see which variables are associated with transition to one of the other two situations. The variable 'time' indicates whether it is the first, second or third measurement moment. The dataset also includes a number of variables, for which I would like to check if this is related to the transition. Some are continuous (cqtarief, mzleef), but the most important one is ordinal with 4 categories (vht). I've tried this code: proc glimmix data=long ic=q; class ID index1 vht relation situation; model situation(ref=first) = relation cqtarief mzleef vht /dist=multinomial link=glogit solution; run; I have the following questions: - I can't include "random index1 / subject=volgnr type=ar(1) residual;" because i have multinomial distribution. How can I model the dependency of the measurements within subjects? Or does the procedure take care of this? - How can I compare models with different covariates? - How do I assess model fit? - Do I need to fit covariance structures (e.g. un/cs/ar(1))? Thanks for any help on this matter!
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