Permutation Covariate Analyses of Residuals Based on Euclidean Distance

Abstract

A new procedure to analyze the results of experimental designs is introduced. A permutation procedure based on Euclidean distance is used to evaluate residuals obtained from least sum of absolute deviations regression. Applications include completely randomized and randomized block configurations including one-way, factorial, split-plot, and Latin square designs, with or without covariates. Parametric assumptions of homogeneity of variance, compound symmetry, and normality are eliminated with this procedure.