title: On two-sample McNemar test.
abstract: Measuring a change in the existence of disease symptoms before and after a treatment is examined for statistical significance by means of the McNemar test. When comparing two treatments, Feuer and Kessler (1989) proposed a two-sample McNemar test. In this article, we show that this test usually inflates the type I error in the hypothesis testing, and propose a new two-sample McNemar test that is superior in terms of preserving type I error. We also make the connection between the two-sample McNemar test and the test statistic for the equal residual effects in a 2 × 2 crossover design. The limitations of the two-sample McNemar test are also discussed.
authors: a Department of Biostatistics , Janssen Research and Development , Raritan , New Jersey , USA.
authors: Jim X
authors: JX
authors: Xiang
mesh_terms: D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000379:methods / Q000706:statistics & numerical data; D003198:Computer Simulation; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D005334:Fever / Q000188:drug therapy; D006801:Humans; D064704:Levofloxacin / Q000008:administration & dosage / Q000627:therapeutic use; D016555:Matched-Pair Analysis; D015233:Models, Statistical; D012107:Research Design / Q000706:statistics & numerical data*; D016896:Treatment Outcome
chemical_list: D000900:Anti-Bacterial Agents; D064704:Levofloxacin
keywords: Asymptotic normality; crossover design; hypothesis testing; paired binary data; pseudolikelihood.