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ERIC Number: EJ746794
Record Type: Journal
Publication Date: 2006
Pages: 29
Abstractor: Author
Reference Count: N/A
ISSN: ISSN-0027-3171
Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables
Song, Xin-Yuan; Lee, Sik-Yum
Multivariate Behavioral Research, v41 n3 p337-365 2006
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the proposed model. Markov chain Monte Carlo methods for obtaining Bayesian estimates and their standard error estimates, highest posterior density intervals, and a PP p value are developed. Results obtained from two simulation studies are reported to respectively reveal the empirical performance of the proposed Bayesian estimation in analyzing complex nonlinear SEMs, and in analyzing nonlinear SEMs with the normal assumption of the exogenous latent variables violated. The proposed methodology is further illustrated by a real example. Detailed interpretation about the interaction terms is presented.
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A