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Copula-based Logistic Regression Models for Bivariate Binary Responses
Volume 12, Issue 3 (2014), pp. 461–476
Xiaohu Li   Linxiong Li   Rui Fang  

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https://doi.org/10.6339/JDS.201407_12(3).0005
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Abstract: 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.

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Keywords
Clayton copula Frank copula Maximum likelihood estimation

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