Multireader multicase variance analysis for binary data

Abstract

Multireader multicase (MRMC) variance analysis has become widely utilized to analyze observer studies for which the summary measure is the area under the receiver operating characteristic (ROC) curve. We extend MRMC variance analysis to binary data and also to generic study designs in which every reader may not interpret every case. A subset of the fundamental moments central to MRMC variance analysis of the area under the ROC curve (AUC) is found to be required. Through multiple simulation configurations, we compare our unbiased variance estimates to naïve estimates across a range of study designs, average percent correct, and numbers of readers and cases.