Estimation Methods For Time-Dependent AUC

Abstract

The area under the receiver operating characteristic (ROC) curve (AUC) is one of the commonly used measure to evaluate or compare the predictive ability of markers to the disease status. Motivated by an angiographic coronary artery disease (CAD) study, our objective is mainly to evaluate and compare the performance of several baseline plasma levels in the prediction of CAD-related vital status over time. Based on censored survival data, the nonparametric estimators are proposed for the time-dependent AUC. The limiting Gaussian processes of the estimators and the estimated asymptotic variance-covariance functions enable us to further construct confidence bands and develop testing procedures. Finally, applications and finite sample properties of the proposed estimation methods and inference procedures are demonstrated through Monte Carlo simulations and the CAD-related death data from the British Columbia Vital Statistics Agency.