A Note on Using the Nonparametric Levene Test When Population Means Are Unequal

Autor/inn/en	Shear, Benjamin R.; Nordstokke, David W.; Zumbo, Bruno D.
Titel	A Note on Using the Nonparametric Levene Test When Population Means Are Unequal
Quelle	In: Practical Assessment, Research & Evaluation, 23 (2018) 13, (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1531-7714
Schlagwörter	Nonparametric Statistics; Computer Simulation; Monte Carlo Methods; Sampling; Error of Measurement + Suchen Sie Ihr Suchwort? Computergrafik; Computersimulation; Monte-Carlo-Methode; Messfehler
Abstract	This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher problem when the populations are normally distributed, and the generalized Behrens-Fisher problem when the populations are nonnormal. The nonparametric Levene test was developed to overcome reductions in power of the original Levene test of equal variances in the case of the generalized Behrens-Fisher problem. We use a Monte Carlo computer simulation to demonstrate that sampling from populations with unequal and unknown means can lead to incorrect (either inflated or decreased) Type I error rates of the nonparametric Levene test. Centering samples using either sample means or medians does not correct the Type I error rates. This note is intended to make applied researchers aware of this problem when testing for the equality of population variances with the NPL test and in general. (As Provided).
Anmerkungen	Dr. Lawrence M. Rudner. e-mail: editor@pareonline.net; Web site: http://pareonline.net
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01