Effect Sizes and Statistical Methods for Meta-Analysis in Higher Education

Autor/in	Bowman, Nicholas A.
Titel	Effect Sizes and Statistical Methods for Meta-Analysis in Higher Education
Quelle	In: Research in Higher Education, 53 (2012) 3, S.375-382 (8 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0361-0365
DOI	10.1007/s11162-011-9232-5
Schlagwörter	Higher Education; Meta Analysis; Effect Size; Statistical Analysis; Regression (Statistics); Comparative Analysis; Scholarship; Models + Suchen Sie Ihr Suchwort? Hochschulbildung; Hochschulsystem; Hochschulwesen; Meta-analysis; Metaanalyse; Statistische Analyse; Regression; Regressionsanalyse; Scholarships; Stipendium; Analogiemodell
Abstract	Quantitative meta-analysis is a very useful, yet underutilized, technique for synthesizing research findings in higher education. Meta-analytic inquiry can be more challenging in higher education than in other fields of study as a result of (a) concerns about the use of regression coefficients as a metric for comparing the magnitude of effects across studies, and (b) the non-independence of observations that occurs when a single study contains multiple effect sizes. This methodological note discusses these two important issues and provides concrete suggestions for addressing them. First, meta-analysis scholars have concluded that standardized regression coefficients, which are often provided in higher education manuscripts, constitute an appropriate metric of effect size. Second, hierarchical linear modeling (HLM) analyses provide an effective method for conducting meta-analytic research while accounting for the non-independence of observations, and HLM is generally superior to other proposed methods that attempt to remedy this same problem. A discussion of how to implement these techniques appropriately is provided. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10