Modified Wilcoxon-Mann-Whitney Test and Power against Strong Null.

IF 1.8 4区 数学 Q1 STATISTICS & PROBABILITY
American Statistician Pub Date : 2019-01-01 Epub Date: 2018-05-10 DOI:10.1080/00031305.2017.1328375
Youyi Fong, Ying Huang
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引用次数: 14

Abstract

The Wilcoxon-Mann-Whitney (WMW) test is a popular rank-based two-sample testing procedure for the strong null hypothesis that the two samples come from the same distribution. A modified WMW test, the Fligner-Policello (FP) test, has been proposed for comparing the medians of two populations. A fact that may be underappreciated among some practitioners is that the FP test can also be used to test the strong null like the WMW. In this paper we compare the power of the WMW and FP tests for testing the strong null. Our results show that neither test is uniformly better than the other and that there can be substantial differences in power between the two choices. We propose a new, modified WMW test that combines the WMW and FP tests. Monte Carlo studies show that the combined test has good power compared to either the WMW and FP test. We provide a fast implementation of the proposed test in an open-source software. Supplementary materials are available online.

Abstract Image

Abstract Image

改进的Wilcoxon-Mann-Whitney检验和抗强零功率。
Wilcoxon-Mann-Whitney (WMW)检验是一种流行的基于秩的双样本检验程序,用于强零假设,即两个样本来自同一分布。提出了一种改进的WMW检验,即Fligner-Policello (FP)检验,用于比较两个种群的中位数。一些从业者可能低估的一个事实是,FP测试也可以用来测试强零,如WMW。在本文中,我们比较了WMW和FP检验在强零值检验中的功率。我们的结果表明,没有一种测试是均匀优于另一种,并且在两种选择之间可能存在实质性的差异。我们提出了一种新的,改进的WMW测试,它结合了WMW和FP测试。蒙特卡罗研究表明,与WMW和FP测试相比,该组合测试具有良好的功率。我们在一个开源软件中提供了一个测试的快速实现。补充资料可在网上查阅。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
American Statistician
American Statistician 数学-统计学与概率论
CiteScore
3.50
自引率
5.60%
发文量
64
审稿时长
>12 weeks
期刊介绍: Are you looking for general-interest articles about current national and international statistical problems and programs; interesting and fun articles of a general nature about statistics and its applications; or the teaching of statistics? Then you are looking for The American Statistician (TAS), published quarterly by the American Statistical Association. TAS contains timely articles organized into the following sections: Statistical Practice, General, Teacher''s Corner, History Corner, Interdisciplinary, Statistical Computing and Graphics, Reviews of Books and Teaching Materials, and Letters to the Editor.
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