I am trying to create an ROC curve using maternal race and smoking group as predictors with depression as the outcome. Below is the syntax, we have used to do this:   ods graphics on; PROC LOGISTIC DATA=d.pramsv1 plots=effect plots=ROC(id=sensit); Class SMOKE2 MATRACE; WHERE (ANSAMPLE=1); MODEL PPDSTATUS(DESC) = SMOKE2 MATRACE; roc 'Smoking with race' SMOKE2 MATRACE; RUN; ods graphics off;   Our output for the ROC curve has several points labelled with their corresponding sensitivity (see below):  Is there a way to determine which cutoffs for the variables correspond to each of these labelled sensitivities?   Any help would be much appreciated! Thanks! ... View more

I am using data from PRAMS (which uses a complex survey design) to create an ROC curve using predicted probabilities. How can I see the sensitivity and specificity for my various cutoffs, keeping in mind the complex sample?   Thanks! ... View more

I am trying to generate an ROC curve using the PROC LOGISTIC procedure (see example below that I am using as a guide): descending data = pinedat plots=effect plots=ROC(id=prob); class alc /descending param = glm; model y = age alc ; roc 'Age' age; roc 'Alcohol' alc; roc 'Age & Alcohol' age alc ; roccontrast reference('Age & Alcohol') /estimate ;    However, my sample is weighted, and I'm not sure how to modify this to be used with PROC SURVEYLOGISTIC. Any help would be much appreciated. Thanks! ... View more