Methodological framework demonstrates structural equation modeling with latent variables, highlighting integrated approaches to account for measurement error in causal analysis.
Model Notation, Covariances, and Path Analysis. Causality and Causal Models. Structural Equation Models with Observed Variables. The Consequences of Measurement Error. Measurement Models: The Relation Between Latent and Observed Variables. Confirmatory Factor Analysis. The General Model, Part I: Latent Variable and Measurement Models Combined. The General Model, Part II: Extensions. Appendices. Distribution Theory. References. Index.
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Clogg et al. (1991) studied this question.
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