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Abstract Details

Activity Number: 232
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #304757
Title: Smoothed Jackknife Empirical Likelihood Inference for ROC Curves with Missing Data
Author(s): Hanfang Yang*+ and Yichuan Zhao
Companies: Georgia State University and Georgia State University
Address: 30 Pryor Street , Altanta, GA, 30303, USA
Keywords: Jackknife ; Smoothed empirical likelihood ; Missing data ; ROC curves

In this paper, we apply smoothed jackknife empirical likelihood (JEL) method to construct confidence intervals for the receiver operating characteristic (ROC) curve with missing data. After using hot deck imputation, we generate pseudo-jackknife sample to develop jackknife empirical likelihood. Comparing to traditional empirical likelihood method, the smoothed JEL has a great advantage in saving computational cost. Under mild conditions, the smoothed jackknife empirical likelihood ratio converges to a scaled chi-square distribution. Furthermore, extensive simulation studies in terms of coverage probability and average length of confidence intervals demonstrate this proposed method has the good performance in small sample sizes. A real data set is used to illustrate our proposed JEL method.

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