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

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...

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Veröffentlicht in:Journal of experimental social psychology 2010-07, Vol.46 (4), p.684-688
Hauptverfasser: Leys, Christophe, Schumann, Sandy
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:0022-1031
1096-0465
DOI:10.1016/j.jesp.2010.02.007