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**Box's M test** is a multivariate statistical test used to check the equality of multiple variance-covariance matrices.

Box's *M* test is susceptible to errors if the data does not meet model assumptions or if the sample size is too large or small.^{[2]} Box's *M* test is especially prone to error if the data does not meet the assumption of multivariate normality.^{[3]}

**^**Box, G.E.P. (1 December 1949). "A General Distribution Theory for a Class of Likelihood Criteria".*Biometrika*.**36**(3–4): 317–346. doi:10.1093/biomet/36.3-4.317.**^**Rebecca M. Warner (2013).*Applied Statistics: From Bivariate Through Multivariate Techniques*. SAGE. p. 778. ISBN 978-1-4129-9134-6.**^**Bryan F.J. Manly (6 July 2004).*Multivariate Statistical Methods: A Primer, Third Edition*. CRC Press. p. 54. ISBN 978-1-58488-414-9.