A New Maximum Test via the Dependent Samples t-Test and the Wilcoxon Signed-Ranks Test
A New Maximum Test via the Dependent Samples t-Test and the Wilcoxon Signed-Ranks Test作者机构：Department of Evaluation and Research Wayne State University Detroit USA Department of Psychology University of Windsor Windsor Canada Department of Evaluation and Research Wayne State University Detroit USA
出 版 物：《Applied Mathematics》 (应用数学（英文）)
年 卷 期：2014年第5卷第1期
页 面：110-114页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Maximum Test Dependent Samples t-Test Wilcoxon Signed-Ranks Test Bonferroni-Dunn Adjustment Experiment-Wise Type I Error Inferential Statistics Monte Carlo Method
摘 要：A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α while guaranteeing the maximum power of the two constituent tests. Critical values, obtained via Monte Carlo methods, are uniformly smaller than the Bonferroni-Dunn adjustment, giving it power superiority when testing for treatment alternatives of shift in location parameter when data are sampled from non-normal distributions.
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