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:

  • Bayes factor;
  • multisample data;
  • structural equation models (SEMs)

Summary

This chapter introduces two-level structural equation models (SEMs) and multisample SEMs, as well as the associated Bayesian methodologies for analyzing two-level and multisample data. It provides a comprehensive framework for analyzing two-level models, nonlinear structural equations are incorporated into the SEMs that are associated with within-group and between-group models. The chapter presents a path sample procedure to compute the Bayes factor for model comparison. One of the main objectives in the analysis of multisample data is to investigate the similarities or differences among the models in the different groups. As a result, the statistical inferences emphasized in analyzing multisample SEMs are different from those in analyzing two-level SEMs.

Controlled Vocabulary Terms

Bayes factors; multiple samples test