I would like to use Proc Glimmix in SAS 9.3 for multivariate generalized linear mixed modeling for two-level data, however I have dependent variables of different types (continuous, binary). Although there is documentation on joint modeling in SAS documentation for non-clustered data, it is unclear to me how joint models can be used with clustered data (e.g., 2-level model, individuals nested within groups, etc.). Also, when using dependent variables of different types, how are the G-side and R-side variances and covariances computed? Could anyone suggest relevant text for reference (preferably with example SAS codes)? Here's the sample code for my 2-level model: proc glimmix data=multi_glmm method=laplace; class dist block; model var = dist dist*IV/noint dist=byobs(dist) solution; random intercept/subject=block type=vc solution cl; covtest zeroG/wald; nloptions gconv=0; run; *data are arranged in long form with two dependent variables (var) of different types (binary, continuous) arranged in successive rows. Any suggestions for improving the code will be greatly appreciated.
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