Nonparametric estimation of conditional ROC curves: Application to discrimination tasks in computerized detection of early breast cancer

A local linear method for estimating the conditional ROC curve under the presence of continuous and categorical covariates is introduced. A data driven smoothing parameter selector based on the bootstrap is proposed. The methods are illustrated with real data from a discrimination problem emerging in the context of computer-aided diagnosis. The bootstrap approach is also used to construct pointwise confidence intervals for the area under the ROC curve.