A Simple Method for Comparing Correlated Roc Curves Using Incomplete Data

Comparative studies of the accuracy of diagnostic procedures often use a paired design to gain in efficiency. Standard methods for analysing data from paired designs require complete observations. In many studies, however, one of the test results may be missing for some patients. In this paper, we propose a simple correction to the existing complete data methods to compare areas under ROC curves derived from paired designs. The approach makes it possible to use the entire available data set in carrying out the comparison, provided that the probability of having both tests does not depend on the test results. As an illustration, we apply our method to the analysis of data from prospective comparison of MRI and ultrasound in detecting periprostatic invasion.