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 (Y_1i, Y_2i). 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.