文章基本信息

标题：Copula-based Logistic Regression Models for Bivariate Binary Responses
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作者：Xiaohu Li ; Linxiong Li ; Rui Fang 等
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2014
卷号：12
期号：3
页码：461-476
出版社：Tingmao Publish Company
摘要：The association between bivariate binary responses has been studied using Pearson’s correlation coefficient, odds ratio, and tetrachoric correlation coefficient. This paper introduces a copula to model the association. Numerical comparisons between the proposed method and the existing methods are presented. Results show that these methods are comparative. However, the copula method has a clearer interpretation and is easier to extend to bivariate responses with three or more ordinal categories. In addition, a goodness-of-fit test for the selection of a model is performed. Applications of the method on two real data sets are also presented.
关键词：Clayton copula; Frank copula; Maximum likelihood estimation; Odds ratio; Tetrachoric correlation.