title: Application of the McNemar test to non-independent matched pair data.
abstract: McNemar's one degree of freedom chi-square test for the equality of proportions appears frequently in the analysis of pairs of matched, binary outcome data (Y1i, Y2i). An assumption underlying this test is that the responses from pair to pair are mutually independent. In certain applications, however, the pairs may represent repeated measurements on the same experimental unit, and hence this assumption is violated. In this paper we suggest an adjustment to the McNemar test to account for the repeated measures clustering effect and we report on a Monte Carlo simulation that evaluates the effectiveness of this approach.
authors.affiliation: Channing Laboratory, Harvard Medical School, Boston, MA 02115.
authors.forename: M
authors.initials: M
authors.lastname: Eliasziw
authors.forename: A
authors.initials: A
authors.lastname: Donner
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D016555:Matched-Pair Analysis; D015233:Models, Statistical; D009010:Monte Carlo Method