Abstract: The receiver operating characteristic (ROC) curve is frequently used to evaluate the accuracy of medical diagnostic tests. Currently, analysis based on the ROC curve has been performed in large public-use data arising from complex survey samples by ignoring the sampling scheme. This paper proposes a nonparametric estimator for the ROC curve that accounts for complex survey sampling. The asymptotic properties of the estimator are developed using empirical process arguments. Simulation studies showed that our proposed estimator performed well in the practical situations we considered, with better performance for larger sample size and disease proportions. The estimator was illustrated in the National Health and Nutrition Examination Survey (NHANES) to evaluate the discrimination of a traditional risk calculator of undiagnosed diabetes.

Key words and phrases: Complex survey data, empirical processes, Horvitz–Thompson estimator, ROC curve.