New Developments in Factor Score Regression: Fit Indices and a Model Comparison Test

Autor/inn/en	Devlieger, Ines; Talloen, Wouter; Rosseel, Yves
Titel	New Developments in Factor Score Regression: Fit Indices and a Model Comparison Test
Quelle	In: Educational and Psychological Measurement, 79 (2019) 6, S.1017-1037 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Devlieger, Ines)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164419844552
Schlagwörter	Regression (Statistics); Computation; Goodness of Fit; Statistical Inference; Structural Equation Models; Statistical Bias; Statistical Analysis; Maximum Likelihood Statistics + Suchen Sie Ihr Suchwort? Regression; Regressionsanalyse; Inferential statistics; Schließende Statistik; Statistische Analyse
Abstract	Factor score regression (FSR) is a popular alternative for structural equation modeling. Naively applying FSR induces bias for the estimators of the regression coefficients. Croon proposed a method to correct for this bias. Next to estimating effects without bias, interest often lies in inference of regression coefficients or in the fit of the model. In this article, we propose fit indices for FSR that can be used to inspect the model fit. We also introduce a model comparison test based on one of these newly proposed fit indices that can be used for inference of the estimators on the regression coefficients. In a simulation study we compare FSR with Croon's corrections and structural equation modeling in terms of bias of the regression coefficients, Type I error rate and power. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01