Dear All, I am using SAS 9.4. I have fit three, 2-level model to my data set using Proc glimmix. as follows: The outcome(Diabetes) and the covariate "bp" are binary variables. Fitted models are : 1- full model with random intercept (A) 2- Full model with both random intercept and random slope(A1) 3- Model A2: excluding the intercation term from fixed level 1 covariates I just wonder how can I compare these three models usyng SAS and tell which model fits better and are more significant I appreciate it very much for your help, ods output fitstatistics=fitA;
title "Model A,random intercept+fixed interactions";
proc glimmix data=data1 noclprint;
class group bp ;
model DIABETES = bmi bp bmi*bp/ solution link=logit dist=binary ddfm=satterthwaite ;
random intercept / type=un subject=group;
weight WEIGHT;
format bp bp.;
format DIABETES DIABETES.;
run; ods output fitstatistics=fitA1; title "Model A,random intercept+fixed interactions"; proc glimmix data=data1 noclprint; class group bp ; model DIABETES = bmi bp bmi*bp/ solution link=logit dist=binary ddfm=satterthwaite ; random intercept bmi/ type=un subject=group; weight WEIGHT; covtest "random slope" . 0 0; format bp bp.; format DIABETES DIABETES.; run; ods output fitstatistics=fitA2; title "Model A,random intercept+fixed interactions"; proc glimmix data=data1 noclprint; class group bp ; model DIABETES = bmi bp / solution link=logit dist=binary ddfm=satterthwaite ; random intercept / type=un subject=group; weight WEIGHT; format bp bp.; format DIABETES DIABETES.; run;
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