A note on dependence modeling for Bernoulli variables

Engin A. Sungur, Jessica M. Orth

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Understanding and modeling multivariate dependence structures depending upon the direction are challenging but an interest of theoretical and applied researchers. In this paper, we propose a characterization of tables generated by Bernoulli variables through the uniformization of the marginals and refer to them as Q-type tables. The idea is similar to the copulas. This approach helps to see the dependence structure clearly by eliminating the effect of the marginals that have nothing to do with the dependence structure. We define and study conditional and unconditional Q-type tables and provide various applications for them. The limitations of existing approaches such as Cochran-Mantel-Haenszel pooled odds ratio are discussed, and a new one that stems naturally from our approach is introduced.

Original languageEnglish (US)
Pages (from-to)8217-8229
Number of pages13
JournalCommunications in Statistics - Theory and Methods
Issue number16
StatePublished - Aug 18 2017

Bibliographical note

Publisher Copyright:
© 2017 Taylor & Francis Group, LLC.


  • Bernoulli variables
  • Cochran-Mantel-Haenszel statistics
  • Conditional Ratio
  • Dependence
  • Directional dependence
  • Odds ratio
  • Risk Ratio


Dive into the research topics of 'A note on dependence modeling for Bernoulli variables'. Together they form a unique fingerprint.

Cite this