Reexamining the Impact of Nonnormality in Two-Group Comparison Procedures

Autor/inn/en	Kang, Yoonjeong; Harring, Jeffrey R.; Li, Ming
Titel	Reexamining the Impact of Nonnormality in Two-Group Comparison Procedures
Quelle	In: Journal of Experimental Education, 83 (2015) 2, S.147-174 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2013.876605
Schlagwörter	Comparative Analysis; Monte Carlo Methods; Statistical Analysis; Robustness (Statistics); Differences; Nonparametric Statistics; Sampling; Statistical Inference; Statistical Distributions + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Statistische Analyse; Widerstandsfähigkeit; Unterscheiden; Inferential statistics; Schließende Statistik; Wahrscheinlichkeitsverteilung
Abstract	The authors performed a Monte Carlo simulation to empirically investigate the robustness and power of 4 methods in testing mean differences for 2 independent groups under conditions in which 2 populations may not demonstrate the same pattern of nonnormality. The approaches considered were the t test, Wilcoxon rank-sum test, Welch-James test with trimmed means and Winsorized variances, and a nonparametric bootstrap test. Results showed that the Wilcoxon rank-sum test and Welch-James test with trimmed means and Winsorized variances were not robust in terms of type I error control when the 2 populations showed different patterns of nonnormality. The nonparametric bootstrap test provided power advantages over the t test. The authors discuss other results from the simulation study and provide recommendations. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01