9. Longitudinal Structural Equation Models

  1. Xin-Yuan Song and
  2. Sik-Yum Lee

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch9

Basic and Advanced Bayesian Structural Equation Modeling: With Applications in the Medical and Behavioral Sciences

Basic and Advanced Bayesian Structural Equation Modeling: With Applications in the Medical and Behavioral Sciences

How to Cite

Song, X.-Y. and Lee, S.-Y. (2012) Longitudinal Structural Equation Models, in Basic and Advanced Bayesian Structural Equation Modeling: With Applications in the Medical and Behavioral Sciences, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118358887.ch9

Author Information

  1. Department of Statistics, The Chinese University of Hong Kong

Publication History

  1. Published Online: 18 JUL 2012
  2. Published Print: 24 AUG 2012

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470669525

Online ISBN: 9781118358887

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Keywords:

  • Bayesian analysis;
  • categorical data;
  • longitudinal SEM;
  • multivariate longitudinal data;
  • two-level nonlinear SEM

Summary

This chapter formulates a longitudinal SEM for analyzing multivariate longitudinal data at different time points. In the Bayesian estimation of the longitudinal two-level nonlinear SEM with missing categorical data, a common strategy is adopted in the Bayesian analysis of SEMs, involving two key steps. The first step is to augment the observed data with all the latent variables and the missing data to form a complete data set and then consider the resulting joint posterior distribution. The second step is to draw a sufficiently large sample of observations from the joint posterior distribution via MCMC methods such as the Gibbs sampler and the MH algorithm. The chapter introduces a general longitudinal two-level nonlinear SEM with covariates for analyzing longitudinal data that involve mixed continuous and ordered categorical observations, as well as missing data.

Controlled Vocabulary Terms

Bayesian inference; Bayesian multivariate linear regression; categorical data; longitudinal study