Multiple McNemar Tests

Peter H. Westfall, James F. Troendle, Gene Pennello

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Methods for performing multiple tests of paired proportions are described. A broadly applicable method using McNemar's exact test and the exact distributions of all test statistics is developed; the method controls the familywise error rate in the strong sense under minimal assumptions. A closed form (not simulation-based) algorithm for carrying out the method is provided. A bootstrap alternative is developed to account for correlation structures. Operating characteristics of these and other methods are evaluated via a simulation study. Applications to multiple comparisons of predictive models for disease classification and to postmarket surveillance of adverse events are given.

Original languageEnglish
Pages (from-to)1185-1191
Number of pages7
Issue number4
StatePublished - Dec 2010


  • Bonferroni-Holm
  • Bootstrap
  • Discreteness
  • Exact tests
  • Multiple comparisons
  • Postmarket surveillance
  • Predictive model


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