Exact Confidence Band for Binormal ROC Curve

In medical practice, the diagnostic accuracy of a biomarker is usually measured by its sensitivity and specificity. The Receiver Operating Characteristic (ROC) curve is the graph of sensitivity against 1? specificity as the cut-off point runs through all possible values. To account for sampling error and make inference about the true ROC curve, the simultaneous confidence band of the whole or partial ROC curve needs to be estimated across all values of specificity within certain range. Particularly, for the binormal ROC curve, there exists two types of confidence band: 1) Working-Hotelling approach and 2) Ellipse-envelope method. However, both are large-sample-based approaches, which do not provide satisfactory coverage for small to median samples. In this paper, we propose a new confidence band for the binormal ROC curve based on the generalized inference approach. Extensive simulation study is carried out to compare the performance of the proposed generalized confidence band with the existing approaches and all methods are applied to a real data set.