Multilevel factor analysis modelling using Markov Chain Monte Carlo (MCMC) estimation
- Latent Variable and Latent Structure Models, Psychology Press, 225-243
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
- Model data structure
- Response types
- Multivariate response model?
- Longitudinal data?
- Further model keywords
- Substantive discipline
- Substantive keywords
Introduces MCMC methods for multilevel factor models
- Paper submitted by
- William Browne, Bristol Veterinary School, University of Bristol, firstname.lastname@example.org