首页    期刊浏览 2024年11月24日 星期日
登录注册

文章基本信息

  • 标题:Copula-based Logistic Regression Models for Bivariate Binary Responses
  • 本地全文:下载
  • 作者:Xiaohu Li ; Linxiong Li ; Rui Fang
  • 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.
国家哲学社会科学文献中心版权所有