1. Introduction

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

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch1

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) Introduction, 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.ch1

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 approach;
  • latent variables;
  • nonparametric structural equation;
  • semiparametric SEMs;
  • structural equation models (SEMs)

Summary

This is the introductory chapter of this book which introduces more advanced structural equation models (SEMs) and emphasizes the Bayesian approach which is more flexible than the covariance structure approach in handling complex data and models. Another objective of this book is to introduce important models that have recently been developed and were not covered by Lee, including innovative growth curve models and longitudinal SEMs for analyzing longitudinal data and for studying the dynamic changes of characteristics with respect to time; semiparametric SEMs for relaxing the normality assumption and for assessing the true distributions of explanatory latent variables; SEMs with a nonparametric structural equation for capturing the true general relationships among latent variables, and transformation SEMs for analyzing highly nonnormal data.

Controlled Vocabulary Terms

Bayesian inference; Bayesian information criterion; latent class model; non-parametric methods