Asymptotic Biases in Exploratory Factor Analysis and Structural Equation Modeling

Autor/in	Ogasawara, Haruhiko
Titel	Asymptotic Biases in Exploratory Factor Analysis and Structural Equation Modeling
Quelle	In: Psychometrika, 69 (2004) 2, S.235-256 (22 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/BF02295942
Schlagwörter	Evaluation Methods; Bias; Factor Analysis; Structural Equation Models; Computation; Predictor Variables; Monte Carlo Methods; Robustness (Statistics); Simulation + Suchen Sie Ihr Suchwort? Faktorenanalyse; Prädiktor; Monte-Carlo-Methode; Widerstandsfähigkeit; Simulation program; Simulationsprogramm
Abstract	Formulas for the asymptotic biases of the parameter estimates in structural equation models are provided in the case of the Wishart maximum likelihood estimation for normally and nonnormally distributed variables. When multivariate normality is satisfied, considerable simplification is obtained for the models of unstandardized variables. Formulas for the models of standardized variables are also provided. Numerical examples with Monte Carlo simulations in factor analysis show the accuracy of the formulas and suggest the asymptotic robustness of the asymptotic biases with normality assumption against nonnormal data. Some relationships between the asymptotic biases and other asymptotic values are discussed. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10