Multiple McNemar Tests


  • Peter H. Westfall,

    Corresponding author
    1. Area of ISQS, Texas Tech University, Lubbock, Texas 79409-2101, U.S.A.
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  • James F. Troendle,

    1. Biostatistics and Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland 20892, U.S.A.
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  • Gene Pennello

    1. US Food and Drug Administration, Epidemiology Branch, Center for Devices and Radiological Health, HFZ-541, 1350 Piccard Drive, Rockville, Maryland 20850, U.S.A.
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Summary 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.