Cluster randomization trials: A simulation study

James X. Song, Chul Ahn

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

A simulation study is conducted to compare several methods that test the common log odds ratio in multiple 2 × 2 tables when the data are correlated within clusters. Allowing cluster size to vary within each table, we evaluate the unadjusted Mantel-Haenszel chi-square statistic (χMH2), the adjusted Mantel-Haenszel chi-square statistics of Rao and Scott using both an unpooled design effect (χRSN2) and a pooled design effect (χRSP2), the adjusted Mantel-Haenszel chi-square statistic of Donald and Donner (χDD2), the chi-square statistic using the GEE approach (χGEE2), the adjusted Mantel-Haenszel chi-square statistic of Begg (χB2), the Wald (χW2), the robust Wald (χRW2), the score (χS2), the robust score (χRS2), and the adjusted Mantel-Haenszel chi-square statistics of Zhang and Boos (χZBP2 and χZBN2). The test statistics above are compared in terms of empirical significance levels and empirical power levels. The robust score statistic χRS2 and the adjusted Mantel-Haenszel chi-square statistics of Zhang and Boos (χZBP2 and χZBN2) generally have empirical significance levels closer to the nominal value than the other statistics. These three statistics have similar empirical power levels when the intrachister correlation is zero or the cluster sizes are balanced. χRS2 performs better in terms of empirical power levels when a positive intracluster correlation exists in the imbalance setting.

Original languageEnglish (US)
Pages (from-to)375-390
Number of pages16
JournalBiometrical Journal
Volume44
Issue number3
DOIs
StatePublished - Aug 19 2002

Keywords

  • Correlated binary data
  • Mantel-Haenszel
  • Randomization trial

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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