Multilevel factor analysis modelling using Markov Chain Monte Carlo (MCMC) estimation

Authors
Goldstein, H. and Browne, W. J.
Year
2002
Journal
Latent Variable and Latent Structure Models, Psychology Press, 225-243
Abstract

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights include coverage of approaches dealing with missing values, semi-parametric estimation, robust analysis, hierarchical data, factor scores, multi-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading researchers in the area will help to stimulate ideas for further research for many years to come.

Number of levels
2
Model data structure
Response types
Multivariate response model?
Yes
Longitudinal data?
No
Further model keywords
Substantive discipline
Substantive keywords
Impact

Introduces MCMC methods for multilevel factor models

Paper submitted by
William Browne, Bristol Veterinary School, University of Bristol, william.browne@bristol.ac.uk
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