A Multivariate Extension of McNemar’s Test Based on Permutations

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...

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Bibliographic Details
Main Author: Grzegorz Kończak
Format: Article
Language:English
Published: Lodz University Press 2020-11-01
Series:Acta Universitatis Lodziensis. Folia Oeconomica
Subjects:
Online Access:https://czasopisma.uni.lodz.pl/foe/article/view/6454
Description
Summary: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 multivariate 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 method of observations was used to estimate the empirical distribution of the test statistics. The considerations 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.
ISSN:0208-6018
2353-7663