Latent variable modelling of categorical data: Tools of analysis for cross-national surveys (LCAT)

Annotated Bibliography (work in progress)
Jouni Kuha, Irini Moustaki, Sally Stares, and Jonathan Jackson
Departments of Methodology and Statistics
London School of Economics and Political Science

Last updated: September 27, 2013

Project funded by the Economic and Social Research Council of United Kingdom, grant RES-239-25-0022, under the Comparative Cross-National Research Methods initiative.

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Contents
1 Background and overviews
1.1 Categorical data analysis with observed variables
1.2 Latent variable modelling
1.3 Cross-national surveys and cross-cultural research
2 Measurement and measurement equivalence in cross-national research
3 Assessing measurement equivalence without latent variable models
4 Multiple-group latent variable modelling: Methodology and overviews
4.1 Overviews and comparisons
4.2 Linear factor analysis and structural equation models
4.3 Latent class models
4.4 Latent trait models
4.5 Sensitivity analyses
5 Multiple-group latent variable modelling: Applications
5.1 Linear factor analysis and structural equation models
5.2 Latent class models
5.3 Latent trait models
6 Model selection for latent class and latent trait models
References