Goodness-of-fit tests for correlated paired binary data

Man Lai TANG, Yan Bo Pei, Weng Kee Wong, Jia Liang Li*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

17 Citations (Scopus)


We review a few popular statistical models for correlated binary outcomes, present maximum likelihood estimates for the model parameters, and discuss model selection issues using a variety of goodness-of-fit test statistics. We apply bootstrap strategies that are computationally efficient to evaluate the performance of goodness-of-fit statistics and observe that generally the power and the type I error rate of the goodness-of-fit statistics depend on the model under investigation. Our simulation results show that careful choice of goodness-of-fit statistics is an important issue especially when we have a small sample and the outcomes are highly correlated. Two biomedical applications are included.

Original languageEnglish
Pages (from-to)331-345
Number of pages15
JournalStatistical Methods in Medical Research
Issue number4
Publication statusPublished - Aug 2012

Scopus Subject Areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

User-Defined Keywords

  • Akaike information criterion
  • bootstrap procedures
  • correlated binary data
  • model selection techniques
  • Rosner's and Dallal's models


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