# GEE - ROC Curves the Same Using Different Cluster Variables

I am creating multiple GEEs with the same covariates, but I am testing different clustering variables. The outcome is a binary yes/no variable and both VAR1 and VAR2 are binary, as well. Patients can be seen at 1 of 7 clinics, and each clinic has multiple doctors. Thus, there is an argument to be made that we should cluster based on clinic or doctor (at this time, we are not considering multiple random effect models). I want to create the ROC curve for both the GEE clustered by clinic and clustered by doctor, but when I do so using this SAS note, I am getting the same ROC curve. I have checked the predicted probabilities, and they are different for the two models. Anyone know what is going on or why this is happening? Appreciate the help and insights.

Here is my code and the outputted ROC curve for both.

*CLUSTERED BY DOCTOR;
PROC GLIMMIX data = DATA ORDER=INTERNAL empirical=root ;
class DOCTOR VAR1 VAR2;
model OUTCOME(event='1')= VAR1|VAR2
/ dist=bin link=logit covb  solution ;
RANDOM _residual_ / SUBJECT=DOCTOR  TYPE=cs  gcorr solution  ;
Run;
proc logistic data=INFO1;
model OUTCOME(event='1') = / nofit;
roc "GLIMMIX model" PRED=phat;
run;

*CLUSTERED BY CLINIC;
PROC GLIMMIX data = DATA ORDER=INTERNAL empirical=root ;
class CLINIC VAR1 VAR2;
model OUTCOME(event='1')= VAR1|VAR2
/ dist=bin link=logit covb  solution ;
RANDOM _residual_ / SUBJECT=CLINIC TYPE=cs  gcorr solution  ;
Run;
proc logistic data=INFO1;
model OUTCOME(event='1') = / nofit;
roc "GLIMMIX model" PRED=phat;
run;