A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

Autor/inn/en	Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.
Titel	A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series
Quelle	In: Psychometrika, 76 (2011) 1, S.77-96 (20 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-010-9189-x
Schlagwörter	Structural Equation Models; Simulation; Behavioral Sciences; Social Sciences; Error of Measurement; Statistical Analysis; Correlation; Evaluation + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Messfehler; Statistische Analyse; Korrelation; Evaluierung
Abstract	Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a sandwich-type standard error estimator of independent data to multivariate time series data. One required element of this estimator is the asymptotic covariance matrix of concurrent and lagged correlations among manifest variables, whose closed-form expression has not been presented in the literature. The performance of the adapted sandwich-type standard error estimator is evaluated using a simulation study and further illustrated using an empirical example. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10