Smoothed jackknife empirical likelihood method for ROC curves with missing data

报告题目Smoothed jackknife empirical likelihood method for ROC curves with missing data

报告人Yichuan Zhao Georgia State University

时间2012 79(星期一)10:00—11:00


摘要:In this talk, 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.   This talk  is based on joint work with Hanfang Yang.

报告人介绍Dr. Yichuan Zhao is currently an associate professor of Statistics in the Georgia State University.  He has a B.S. and a M.S. in Mathematics from Peking University, and a M.S. in Stochastics and Operations Research from the Utrecht University. He received the Ph. D. in Statistics  at the Florida State University. His current research interest focuses on Survival Analysis, Empirical Likelihood, Analysis of ROC Curves, Bioinformatics, and Statistical Modeling of Fuzzy Systems.  He has a joint appointment as Associate Member of the Neuroscience Institute in the  Georgia State University.


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