Box's M test
Box's M test is a multivariate statistical test used to check the equality of multiple variance-covariance matrices.[1] The test is commonly used to test the assumption of homogeneity of variances and covariances in MANOVA and linear discriminant analysis. It is named after George E. P. Box.
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]
See also
References
- ^ 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: 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.
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