Exact tests for one sample correlated binary data

Seung Ho Kang, Sang Jin Chung, Chul W. Ahn

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this paper we developed exact tests for one sample correlated binary data whose cluster sizes are at most two. Although significant progress has been made in the development and implementation of the exact tests for uncorrelated data, exact tests for correlated data are rare. Lack of a tractable likelihood function has made it difficult to develop exact tests for correlated binary data. However, when cluster sizes of binary data are at most two, only three parameters are needed to characterize the problem. One parameter is fixed under the null hypothesis, while the other two parameters can be removed by both conditional and unconditional approaches, respectively, to construct exact tests. We compared the exact and asymptotic p-values in several cases. The proposed method is applied to real-life data.

Original languageEnglish (US)
Pages (from-to)188-193
Number of pages6
JournalBiometrical Journal
Volume47
Issue number2
DOIs
StatePublished - Apr 2005

Keywords

  • Clustered data
  • Dichotomous data
  • Exchangeability
  • Intraclass correlation coefficient
  • Ophthalmology
  • Otolaryngology
  • Paired samples
  • Twin study

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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