How to calculate a confusion matrix (or ROC curve) from GLIMMIX OUTPUT statement

[issac]

Hi folks;

I'm trying to fit a hierarchical logistic regression with GLIMMIX procedure that allows for random effect at level-1 unit (here in my case is patient id). Here is the code:

* data is sorted by id;

ods html close;

ods html;

proc glimmix

     class id sex;

     model label= sex score / dist=binary link=logit;

     random id;

     output out=out1 predpredicted;

run;

where "score" is a continuous predictor and "label" is the binary class of patients (0: died and 1: survived). Now the question is how I can calculate a confusion matrix (table of actual versus predicted class labels) from this fitting?

Thanks!

Issacglimix

[Reeza]

If you took the predicted output and ran a proc freq would that give you your confusion matrix?

[issac]

@Reeza

Thanks. It's a good hint to use proc freq after proc glimmix. But honestly I am not sure which of "Pred" or "PredPA" is the best option for doing the job. Could you explain further?