This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 126
Type: Contributed
Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #308437
Title: Estimation of the Area Under ROC Curve with Censored Data
Author(s): Lili Yao* and Qihua Wang+
Companies: Northwestern University and Chinese Academy of Sciences
Address: , , ,
Keywords: ROC curve ; Censored data ; AUC ; Plug in ; Asymptotically normal
Abstract:

The Receiver Operating Characteristics(ROC)curve is the graphic plot of sensitivity against (1-specificity) for a binary classifier as its discrimination threshold is varied. The area under the ROC curve is the most commonly used summary measure of diagnostic accuracy for a continuous-scale diagnostic test. In this paper, we develop methods to estimate the area under the ROC curve (AUC) with censored data. Based on two different integration representations of this parameter, two nonparametric estimators are defined by the "plug in" method. Both the proposed estimators are shown to be asymptotically normal based on counting process and martingale theory. Our simulation study confirms the performances of the proposed estimators with small sample size in terms of biases, standard error and mean square error.


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