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The purpose of this publication is to propose a permutation test to detect the departure from symmetry in multidimensional contingency tables. The proposal is a multivariate extension of McNemar’s test. McNemar’s test could be applied to 2 × 2 contingency tables. The proposal may be also treated as a modification of Cochran’s Q test which is used for testing dependency for multi‐ variate binary data. The form of the test statistics that allows us to detect the departure from counts symmetry in multidimensional contingency tables is presented in the article. The permutation meth‐ od of observations was used to estimate the empirical distribution of the test statistics. The consid‐ erations were supplemented with examples of the use of a multivariate test for simulated and real data. The application of the proposed test allows us to detect the asymmetrical distribution of counts in multivariate contingency tables.

A Multivariate Extension of McNemar’s Test Based on Permutations