JSM 2005 Online Program

Abstract #303288

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Activity Number:	32
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Biometrics Section
Abstract - #303288
Title:	Empirical Likelihood-based Inference for the Area Under the ROC Curve
Author(s):	Gengsheng Qin*+ and Xiao-Hua (Andrew) Zhou
Companies:	Georgia State University and University of Washington
Address:	Department of Math and Stat, Atlanta, GA, 30303, United States
Keywords:	ROC ; AUC ; Diagnostic test ; Placement value ; Confidence interval
Abstract:	For a continuous-scale diagnostic test, the most commonly used summary index of the receiver operating characteristic (ROC) curve is the area under the curve (AUC) that measures the accuracy of the diagnostic test. In this paper, we propose an empirical likelihood approach for the inference of AUC. We first define an empirical likelihood ratio for AUC and show its limiting distribution is a scaled chi-square distribution. We then obtain an empirical likelihood-based confidence interval for AUC using the scaled chi-square distribution. This empirical likelihood inference for AUC can be extended to stratified samples. The resulting limiting distribution is a weighted sum of independent chi-square distributions. We also conduct simulation studies to compare the relative performance of the proposed empirical likelihood-based interval with the existing normal approximation-based intervals for AUC.

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