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PubMed · 12353797

Multivariate multiple regression analyses: a permutation method for linear models.

Paul W Mielke·Kenneth J Berry
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Abstract

A multivariate extension of a univariate procedure for the analysis of experimental designs is presented. A Euclidean-distance permutation procedure is used to evaluate multivariate residuals obtained from a regression algorithm, also based on Euclidean distances. Applications include various completely randomized and randomized block experimental designs such as one-way, Latin square, factorial, nested, and split-plot designs, with and without covariates. Unlike parametric procedures, the only required assumption is the randomization of subjects to treatments.

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Paul W Mielke, Kenneth J Berry. 2002. Multivariate multiple regression analyses: a permutation method for linear models.. https://doi.org/10.2466/pr0.2002.91.1.3

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