Estimation and Comparison of Receiver Operating Characteristic Curves

Abstract

The receiver operating characteristic (ROC) curve displays the capacity of a marker or diagnostic test to discriminate between two groups of subjects, cases versus controls. We present a comprehensive suite of Stata commands for performing ROC analysis. Nonparametric, semiparametric, and parametric estimators are calculated. Comparisons between curves are based on the area or partial area under the ROC curve. Alternatively, pointwise comparisons between ROC curves or inverse ROC curves can be made. We describe options to adjust these analyses for covariates and to perform ROC regression in a companion article. We use a unified framework by representing the ROC curve as the distribution of the marker in cases where we have standardized it to the control reference distribution.