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ERIC Number: EJ772383
Record Type: Journal
Publication Date: 2007
Pages: 31
Abstractor: Author
Reference Count: N/A
ISSN: ISSN-1070-5511
Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables
Lee, Sik-Yum; Song, Xin-Yuan; Tang, Nian-Sheng
Structural Equation Modeling: A Multidisciplinary Journal, v14 n3 p404-434 2007
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.
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:
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A