Please I wish to know whether there is SAS code, on GLIMMIX to  handle when the proportional odds assumptions is not verified. So I wish to model the ordinal outcome with different slopes, taking into consideration the random effects.  Thanks ... View more

Greetings community, am trying to do multiple imputation and I which to have pooled estimates through the function MIANALYZE by region, but I don't how to include that in my code proc mi nimpute=2 data=Work.query seed=45 out=want_imp1; class age7 sgp region province ghq12 sex; fcs regression (lnbmi) logistic (sgp) discrim (province) ; var id hh wfin age7 lnbmi ghq12 province region sgp sex; run ; proc mixed data= want_imp1; title 'PROC MIXED weighted + clustered GP after MI'; by _imputation_ regionch; weight wfin; class hh age7 sex sgp ; model lnbmi = GHQ12 sgp sex*age7 / solution covb; random intercept / subject=hh; ods output SolutionF = mixed_GP_parms covb = mixed_GP_cov; run; proc mianalyze parms=mixed_gp_parms ; title 'MIANALYZE of MIXED with GP as covariate'; class sgp sex age7 ; modeleffects intercept sgp age7*sex; by region run;   Thanks very much. ... View more

Greetings everyone  I have a dataset with a variable with missing values called NA. Because of this, it makes that variable a character variable, so I don't know how to make this numerical so that I can use multiple imputations to impute the missing data.  But I removed the Na and replaced it with a space; it still shows that the variable is a character variable, same with the replacing with the dot,  Please, what can I do to handle this? Thanks. ... View more