11. Structural Equation Models with Mixed Continuous and Unordered Categorical Variables

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

Published Online: 18 JUL 2012

DOI: 10.1002/9781118358887.ch11

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 Mixed Continuous and Unordered Categorical 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.ch11

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:

  • SEM with mixed continuous/unordered categorical variables;
  • gene–gene/gene–environment in complex disease pathogenesis;
  • pathogenetic pathway complexity;
  • SEMs, genotype/phenotype interrelationship;
  • CFA, mean vector and factor loading for multinomial modeling;
  • nonlinear SEM with mixed continuous/unordered variables;
  • multilocus genotyping assay, SNPs assessed;
  • factor, Bayesian model selection statistic, in parametric SEMs;
  • methodology, for studies of diabetic kidney disease;
  • MCMC sampling difficulty, alleviated by data augmentation

Summary

This chapter contains sections titled:

  • Introduction

  • Parametric SEMs with continuous and unordered categorical variables

  • Bayesian semiparametric SEM with continuous and unordered categorical variables

  • Appendix 11.1: Full conditional distributions

  • Appendix 11.2: Path sampling

  • Appendix 11.3: A modified truncated DP related to equation (11.19)

  • Appendix 11.4: Conditional distributions and the MH algorithm for the Bayesian semiparametric model

  • References