10. Semiparametric Structural Equation Models with Continuous Variables

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

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch10

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) Semiparametric Structural Equation Models with Continuous Variables, 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.ch10

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:

  • semiparametric SEMs with continuous variables;
  • SEMs and latent variables, measurement/structural equations;
  • latent variable estimation, nonparametric/semiparametric;
  • semiparametric methods in handling general nonnormal data;
  • Bayesian semiparametric in SEM analysis;
  • Bayesian semiparametric hierarchical modeling of SEMs, with covariates;
  • simulation study, empirical performance of semiparametric;
  • Lν-measure performance in model comparison;
  • Lν-measure via WinBUGS and R2WinBUGS;
  • Bayesian, and explanatory latent variable effects

Summary

This chapter contains sections titled:

  • Introduction

  • Bayesian semiparametric hierarchical modeling of SEMs with covariates

  • Bayesian estimation and model comparison

  • Application: Kidney disease study

  • Simulation studies

  • Discussion

  • Appendix 10.1: Conditional distributions for parametric components

  • Appendix 10.2: Conditional distributions for nonparametric components

  • References