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A Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects

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  • Song, Xin-Yuan
  • Tang, Nian-Sheng
  • Chow, Sy-Miin

Abstract

This paper proposes a generalized random coefficient structural equation model for analyzing longitudinal data by incorporating the correlated structure due to adjacent time effects and by allowing structural parameters to vary across individuals. The coregionalization for modeling multivariate spatial data is adopted to formulate the correlated structure between adjacent time points. A Bayesian approach coupled with the Gibbs sampler and the Metropolis–Hastings algorithm is developed to obtain the Bayesian estimates of unknown parameters and latent variables simultaneously. A simulation study and a real example related to an emotion study are presented to illustrate the newly developed methodology.

Suggested Citation

  • Song, Xin-Yuan & Tang, Nian-Sheng & Chow, Sy-Miin, 2012. "A Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4190-4203.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:12:p:4190-4203
    DOI: 10.1016/j.csda.2012.04.016
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    References listed on IDEAS

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    3. Hogan J.W. & Tchernis R., 2004. "Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 314-324, January.
    4. Sanchez, Brisa N. & Budtz-Jorgensen, Esben & Ryan, Louise M. & Hu, Howard, 2005. "Structural Equation Models: A Review With Applications to Environmental Epidemiology," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1443-1455, December.
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    6. W. R. Gilks & N. G. Best & K. K. C. Tan, 1995. "Adaptive Rejection Metropolis Sampling Within Gibbs Sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(4), pages 455-472, December.
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    Cited by:

    1. Junhao Pan & Edward Haksing Ip & Laurette Dubé, 2020. "Multilevel Heterogeneous Factor Analysis and Application to Ecological Momentary Assessment," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 75-100, March.

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