Methodological Measurement Fruitfulness of Exploratory Structural Equation Modeling (ESEM): New Approaches to Key Substantive Issues in Motivation and Engagement

Autor/inn/en	Marsh, Herbert W.; Liem, Gregory Arief D.; Martin, Andrew J.; Morin, Alexandre J. S.; Nagengast, Benjamin
Titel	Methodological Measurement Fruitfulness of Exploratory Structural Equation Modeling (ESEM): New Approaches to Key Substantive Issues in Motivation and Engagement
Quelle	In: Journal of Psychoeducational Assessment, 29 (2011) 4, S.322-346 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0734-2829
DOI	10.1177/0734282911406657
Schlagwörter	Structural Equation Models; Factor Analysis; Factor Structure; Correlation; Goodness of Fit; Measures (Individuals); Students; Foreign Countries; Australia + Suchen Sie Ihr Suchwort? Faktorenanalyse; Faktorenstruktur; Korrelation; Messdaten; Student; Schüler; Schülerin; Studentin; Ausland; Australien
Abstract	The most popular measures of multidimensional constructs typically fail to meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors that are not so highly correlated as to detract from their discriminant validity. Part of the problem, the authors argue, is undue reliance on overly restrictive independent cluster models of confirmatory factor analysis (ICM-CFA) in which each item loads on one, and only one, factor. Here the authors demonstrate exploratory structural equation modeling (ESEM), an integration of the best aspects of CFA and traditional exploratory factor analyses (EFA). On the basis of responses to the 11-factor Motivation and Engagement Scale (n = 7,420, M[subscript age] = 14.22), we demonstrate that ESEM fits the data much better and results in substantially more differentiated (less correlated) factors than corresponding CFA models. Guided by a 13-model taxonomy of ESEM full-measurement (mean structure) invariance, the authors then demonstrate invariance of factor loadings, item intercepts, item uniquenesses, and factor variances-covariances, across gender and over time. ESEM has broad applicability to other areas of research that cannot be appropriately addressed with either traditional EFA or CFA and should become a standard tool for use in psychometric tests of psychological assessment instruments. (Contains 6 tables and 1 figure.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10