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ERIC Number: EJ921794
Record Type: Journal
Publication Date: 2011
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1070-5511
EISSN: N/A
A Bayesian Approach for Analyzing Longitudinal Structural Equation Models
Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum
Structural Equation Modeling: A Multidisciplinary Journal, v18 n2 p183-194 2011
This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically changed over time. The second level is defined for individuals for assessing their characteristics that are invariant with time. The proposed longitudinal structural equation model also accommodates missing data. A Bayesian approach is developed for estimation of parameters and model comparison. The newly developed methodologies are applied to a longitudinal study concerning cocaine use. (Contains 1 figure and 2 tables.)
Psychology Press. 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
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A