Relative Power of the Wilcoxon Test, the Friedman Test, and Repeated-Measures ANOVA on Ranks
Relative Power of the Wilcoxon Test, the Friedman Test, and Repeated-Measures ANOVA on Ranks
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DOI：
10.1080/00220973.1993.9943832
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发表时间：
1993-07
影响因子：
2.2
通讯作者：
D. W. Zimmerman;B. Zumbo
中科院分区：
文献类型：
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作者：
D. W. Zimmerman;B. Zumbo
许多教育学、心理学和社会科学的统计学入门教科书都认为弗里德曼检验是重复测量方差分析的非参数对应，就像克鲁斯卡尔-沃利斯检验是单因素方差分析的对应一样。然而，在理论统计学中，弗里德曼检验是符号检验的推广，并且对于正态分布和许多非正态分布具有符号检验的适度统计功效。尽管研究人员并不熟悉，但另一个可被视为重复测量方差分析的非参数对应物的显著性检验是等级转换程序，其中对等级进行通常的参数统计分析，替换原始分数。在目前的计算机模拟研究中，我们比较了普通的配对样本学生t检验，Wilcoxon符号秩检验，和符号检验的相关样本从正常的，均匀的，混合正态的，指数，拉普拉斯，柯西分布，其中t.
Abstract Many introductory statistics textbooks in education, psychology, and the social sciences consider the Friedman test to be a nonparametric counterpart of repeated-measures ANOVA, just as the Kruskal-Wallis test is a counterpart of oneway ANOVA. However, it is known in theoretical statistics that the Friedman test is a generalization of the sign test and possesses the modest statistical power of the sign test for normal as well as many nonnormal distributions. Although not familiar to researchers, another significance test that can be regarded as a nonparametric counterpart of repeated-measures ANOVA is a rank-transformation procedure, in which the usual parametric statistical analysis is performed on ranks replacing the original scores. In the present computer simulation study we compared the ordinary paired-samples Student t test, the Wilcoxon signed-ranks test, and the sign test for correlated samples from normal, uniform, mixed-normal, exponential, Laplace, and Cauchy distributions, for which t...