A Goodness-of-Fit Test for Logistic Regression Models in Stratified Case-Control Studies via Empirical Likelihood |
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Authors: | Shuwen Wan Xin Deng Biao Zhang |
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Affiliation: | 1. Department of Applied Mathematics , Nanjing University of Finance &2. Economics , Nanjing , China wanshuwen@yahoo.com.cn;4. PRA International, Ridge Drive , Lenexa , KS , U.S.A.;5. Department of Mathematics , University of Toledo , Toledo , OH , U.S.A. |
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Abstract: | In the literature, there were only a few reports on goodness-of-fit tests on logistic regression models specifically derived for case-control studies. In this article, we propose a goodness-of-fit test for logistic regression models in stratified case-control studies using an empirical likelihood approach. The proposed statistic is an alternative to the statistic G o , recently proposed by Arbigast and Lin (2005 Arbigast , P. G. , Lin , D. Y. ( 2005 ). Model-checking techniques for stratified case-control studies . Statist. Med. 24 : 229 – 247 . [Google Scholar]). Simulation results show that the proposed statistic is often slightly more powerful than G o , although their performances are always close to each other. Moreover, implementation of our method is easy since the usual stratified logistic regression procedures in many statistical softwares can be employed. Some asymptotic results and application of the proposed statistic to two real datasets are also presented. |
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Keywords: | Density ratio model Empirical likelihood Goodness-of-fit Logistic regression Stratified case-control study |
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