ROC curves (receiver operating characteristic curves) are commonly used to portray the performance of detectors in signal-detection tasks, such as intrusion detection. This report introduces the origins of signal-detection-theory, and the underpinnings of ROC curves. It provides examples of how to construct these curves, as well as how to measure, interpret and compare them. Information about a...

Receiver operating characteristic (ROC) curves play a central role in the evaluation of biomarkers and tests for disease diagnosis. Predictors for event time outcomes can also be evaluated with ROC curves, but the time lag between marker measurement and event time must be acknowledged. We discuss different definitions of time-dependent ROC curves in the context of real applications. Several app...

A synthesis of the empirical Bayes method and the method of estimating equations is used to combine individual receiver operating characteristic (ROC) area estimates from different studies of the same diagnostic test into a single estimate. This single estimate represents the population mean from which individual areas under the ROC curves were sampled. The only data needed to carry out the met...

The comparison of Receiver Operating Characteristic (ROC) curves is frequently used in the literature to compare discriminatory capability different classification procedures based on diagnostic variables. performance these variables can be sometimes influenced by presence other covariates, and thus they should taken into account when making comparison. A new non-parametric test proposed here f...