A Binomial Test of Group Differences with Correlated Outcome Measures

Autor/inn/en	Onwuegbuzie, Anthony J.; Levin, Joel R.; Ferron, John M.
Titel	A Binomial Test of Group Differences with Correlated Outcome Measures
Quelle	In: Journal of Experimental Education, 79 (2011) 2, S.127-142 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
Schlagwörter	Hypothesis Testing; Statistical Analysis; Effect Size; Probability; Error of Measurement; Correlation; Differences; Children; Foreign Countries; Israel; Child Behavior Checklist + Suchen Sie Ihr Suchwort? Hypothesenprüfung; Hypothesentest; Statistische Analyse; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Messfehler; Korrelation; Unterscheiden; Child; Kind; Kinder; Ausland
Abstract	Building on previous arguments for why educational researchers should not provide effect-size estimates in the face of statistically nonsignificant outcomes (Robinson & Levin, 1997), Onwuegbuzie and Levin (2005) proposed a 3-step statistical approach for assessing group differences when multiple outcome measures are individually analyzed within the same study. One suggested Step 3 strategy was to conduct a binomial (or "sign") test of the number of between-group outcome mean differences that are in the same direction. However, because multiple measures within a study typically are correlated, the binomial test's independence assumption will be violated. In the present investigation, the authors (a) performed a Monte Carlo simulation study to assess the Type I error behavior of the binomial test under varying degrees of independence-assumption violations, resulting in a table of adjusted critical values; and (b) illustrated use of this table by applying its adjusted critical values to a real research example. (Contains 3 tables and 5 footnotes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10