A New Maximum Test via the Dependent Samples t-Test and the Wilcoxon Signed-Ranks Test

• 作者: Saverpierre Maggio Shlomo S. Sawilowsky
• 来源期刊: 应用数学(英文)
• 学科: 医学
• 关键词: MAXIMUM TEST DEPENDENT SAMPLES T-TEST Wilcoxon Signed-Ranks TEST Bonferroni-Dunn Adjustment Experiment-Wise Type I Error Inferential Statistics Monte Carlo Method
• 年，卷（期）: 2014,（1）
• 页码范围: 110-114
• 页数: 5页
• 分类号: R73

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.