JSM 2005 Online Program

Abstract #304255

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	451
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor:	IMS
Abstract - #304255
Title:	An Application of Empirical Processes to ROC Curve
Author(s):	Costel Chirila*+ and Arne Bathke and Arnold J. Stromberg
Companies:	University of Kentucky and University of Kentucky and University of Kentucky
Address:	202 Patchen Drive Apt 105, Lexington, KY, 40517, United States
Keywords:	empirical processes ; functional delta method ; ROC ; AUC
Abstract:	The ROC curve is the plot of sensitivity vs. 1-specificity of a quantitative diagnostic test for a range of cut-off points. The nonparametric estimator of the curve is the empirical ROC curve. The AUC (area under the curve) is mainly used to asses the performance of the diagnostic test. The empirical AUC is proven by Hanley and McNeil to be the Mann-Whitney functional. Asymptotic properties of these estimators were first developed by Hsieh and Turnbull in 1996 based on quantile process theory. In this presentation, we will approach the asymptotic distributions using modern empirical processes theory and the functional delta method. The advantage of this approach is it can be used for different sampling schemes (i.e., censored data, truncated data). It also can be generalized to the multivariate case when more than one diagnostic test is used to derive a ROC curve.

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