Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables

Autor/inn/en	Lee, Sik-Yum; Song, Xin-Yuan; Tang, Nian-Sheng
Titel	Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables
Quelle	In: Structural Equation Modeling: A Multidisciplinary Journal, 14 (2007) 3, S.404-434 (31 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1070-5511
Schlagwörter	Interaction; Structural Equation Models; Bayesian Statistics; Computation; Computer Software; Computer Simulation; Sample Size + Suchen Sie Ihr Suchwort? Interaktion; Computergrafik; Computersimulation
Abstract	The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. This approach produces a Bayesian estimate that has the same statistical optimal properties as a maximum likelihood estimate. Other advantages over the traditional approaches are discussed. More important, we demonstrate through examples how to use the freely available software WinBUGS to obtain Bayesian results for estimation and model comparison. Simulation studies are conducted to assess the empirical performances of the approach for situations with various sample sizes and prior inputs. (Author).
Anmerkungen	Lawrence Erlbaum. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals/default.html
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10