3. Bayesian Methods for Estimating Structural Equation Models

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

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch3

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) Bayesian Methods for Estimating 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.ch3

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

SEARCH

Keywords:

  • Bayesian, in estimating SEMs;
  • covariance structure analysis;
  • Bayesian approach and flexibility;
  • Bayesian methods, and MCMC algorithms;
  • Bayesian and ML, asymptotically equivalent;
  • conjugate prior distribution;
  • data-dependent prior inputs;
  • SEMs, random latent variables and data augmentation;
  • Bayesian estimation via WinBUGS

Summary

This chapter contains sections titled:

  • Introduction

  • Basic concepts of the Bayesian estimation and prior distributions

  • Posterior analysis using Markov chain Monte Carlo methods

  • Application of Markov chain Monte Carlo methods

  • Bayesian estimation via WinBUGS

  • Appendix 3.1: The gamma, inverted gamma, Wishart, and inverted Wishart distributions and their characteristics

  • Appendix 3.2: The Metropolis–Hastings algorithm

  • Appendix 3.3: Conditional distributions [Ω|Y, θ] and [θ|Y,Ω]

  • Appendix 3.4: Conditional distributions [Ω|Y, θ] and [θ|Y,Ω] in nonlinear SEMs with covariates

  • Appendix 3.5: WinBUGS code

  • Appendix 3.6: R2WinBUGS code

  • References