title: Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.
abstract: Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure.
authors.affiliation: Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island, U.S.A.
authors.forename: Eunhee
authors.initials: E
authors.lastname: Kim
authors.forename: Zheng
authors.initials: Z
authors.lastname: Zhang
authors.forename: Youdan
authors.initials: Y
authors.lastname: Wang
authors.forename: Donglin
authors.initials: D
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D015588:Observer Variation; D012372:ROC Curve; D015203:Reproducibility of Results; D012107:Research Design
keywords: Multi-reader; Multi-test design; Power; Receiver operating characteristic curve; Sample size; U-statistics