A nonparametric method to analyze interactions: The adjusted rank transform test

被引:112
作者
Leys, Christophe [1 ]
Schumann, Sandy [1 ]
机构
[1] Univ Libre Bruxelles, Social Psychol Unit, B-1050 Brussels, Belgium
关键词
Nonparametric test; Factorial design; Interaction; Rank test; Adjusted rank transformation; VARIANCE; DESIGN; CONSEQUENCES; ALTERNATIVES; ASSUMPTION; COVARIANCE; TRENDS;
D O I
10.1016/j.jesp.2010.02.007
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Experimental social psychologists routinely rely on ANOVA to study interactions between factors even when the assumptions underlying the use of parametric tests are not met Alternative nonparametric methods are often relatively difficult to conduct, have seldom been presented into detail in regular curriculum and have the reputation - sometimes incorrectly - of being less powerful than parametric tests This article presents the adjusted rank transform test (ART), a nonparametric test, easy to conduct, having the advantage of being much more powerful than parametric tests when certain assumptions underlying the use of these tests are violated To specify the conditions under which the adjusted rank transform test is superior to the usual parametric tests, results of a Monte Carlo simulation are presented (C) 2010 Elsevier Inc All rights reserved
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页码:684 / 688
页数:5
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