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Statistical Significance Levels of Nonparametric Tests Biased by Heterogeneous Variances of Treatment Groups
Authors:Donald W. Zimmerman
Affiliation:Carleton University
Abstract:The statistical significance levels of the Wilcoxon-Mann-Whitney test and the Kruskal-Wallis test are substantially biased by heterogeneous variances of treatment groups—even when sample sizes are equal. Under these conditions, the Type I error probabilities of the nonparametric tests, performed at the .01, .05, and .10 significance levels, increase by as much as 40%-50% in many cases and sometimes as much as 300%. The bias increases systematically as the ratio of standard deviations of treatment groups increases and remains fairly constant for various sample sizes. There is no indication that Type I error probabilities approach the significance level asymptotically as sample size increases.
Keywords:homogeneity of variance  Kruskal-Wallis test  nonparametric tests  rank-randomization  significance level  statistical significance tests  Student t test  Type I error  Wilcoxon-Mann-Whitney test
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