Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality

Autor/inn/en	Fan, Weihua; Hancock, Gregory R.
Titel	Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality
Quelle	In: Journal of Educational and Behavioral Statistics, 37 (2012) 1, S.137-156 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998610396897
Schlagwörter	Robustness (Statistics); Hypothesis Testing; Monte Carlo Methods; Simulation; Error of Measurement; Statistical Analysis; Structural Equation Models; Sample Size; Effect Size + Suchen Sie Ihr Suchwort? Widerstandsfähigkeit; Hypothesenprüfung; Hypothesentest; Monte-Carlo-Methode; Simulation program; Simulationsprogramm; Messfehler; Statistische Analyse
Abstract	This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust estimation/rescaling strategies in order to alleviate reliance on normality. A Monte Carlo simulation is conducted to compare the Type I error rate and the power of the proposed six RMM test statistics to five analysis of variance (ANOVA)-based statistics, the latter of which have also employed trimmed means and Winsorized variances to enhance robustness. Various simulation factors manipulated include variance inequality, sample-size pairings with group variances, degree of nonnormality, alpha level for hypothesis tests, and effect size. Results show that the proposed RMM methods are indeed superior to the traditional ANOVA-based methods. (Contains 3 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10