6. Structural Equation Models with Hierarchical and Multisample Data

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

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch6

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) Structural Equation Models with Hierarchical and Multisample Data, 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.ch6

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:

  • SEMs with hierarchical/multisample data;
  • two-level SEMs and multisample SEMs;
  • Bayesian in two-level/multisample data;
  • algorithm based on Gibbs sampler and MH algorithm;
  • accommodating mixed ordered/continuous variables;
  • Bayesian for two-level nonlinear SEM with mixed continuous;
  • latent psychological determinants, CSWs risk behavior in AIDS;
  • WinBUGS software, two-level nonlinear SEM Bayesian estimate;
  • structural equation models with multisample data;
  • MH algorithm, two-level nonlinear SEM

Summary

This chapter contains sections titled:

  • Introduction

  • Two-level structural equation models

  • Structural equation models with multisample data

  • Appendix 6.1: Conditional distributions: Two-level nonlinear SEM

  • Appendix 6.2: The MH algorithm: Two-level nonlinear SEM

  • Appendix 6.3: PP p-value for two-level nonlinear SEM with mixed continuous and ordered categorical variables

  • Appendix 6.4: WinBUGS code

  • Appendix 6.5: Conditional distributions: Multisample SEMs

  • References