Dear SteveDenham, first of all, thank you for your detailed answer and your insight. Instead of "group", I added (time) in the brackets to compare the different means of the IDs between all time stamps. After adding your suggestions and a few specifications, my code looks like this: *generic QoL
***************;
PROC GLIMMIX data=daten.mixed;
CLASS id group time (ref="0") sex (ref="1") age_cat (ref="1") smoker_cat(ref="3") ACT_ges (ref="5");
MODEL eq5d5l = time group sex age_cat smoker_cat ACT_ges /dist=beta link=logit alpha=0.05 solution cl;
LSMEANS time / cl ilink diff=control;
RANDOM intercept / subject=id (time) type=ar(1) residual;
store daten.eq5d5l_mixed;
run; quit;
/* */
/* %NLMeans(instore=daten.eq5d5l_mixed, coef=coeffs, link=logit, title=Difference of HRQoL); */
*total costs
***************;
*Assign a small amount to consider in the gamma model;
data daten.mixed_costs; set daten.mixed;
if costs=0 and cc=1 then do; costs =1; end;
run;
*Mixed Model;
PROC GLIMMIX data=daten.mixed_costs;
CLASS id group time (ref="0") sex (ref="1") age_cat (ref="1") smoker_cat(ref="3") employment (ref="1") ACT_ges (ref="5");
MODEL total costs = group time sex age_cat smoker_cat FIM4_t0 ACT_ges /dist=gamma link=log alpha=0.05 solution cl;
LSMEANS time / cl ilink diff=control;
RANDOM intercept / subject=id(time) type=ar(1) residual;
store daten.cost_mixed;
run; quit; Model EQ5D: After adapting these changes, to log-Output says: NOTE: Did not converge. Do you have an idea what's wrong? Model Costs: Unfortunately, the model I still not working, maybe it has something to do with the estimation method. How do I know which method is appropriate? Thanks in advance and have a great day! Maria
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