Hagenaars-McCutcheon (2002) Applied Latent Class Analysis

Summary

Applied Latent Class Analysis (Cambridge University Press, 2002), edited by Jacques A. Hagenaars and Allan L. McCutcheon, is a reference volume on latent class models for categorical data, spanning model formulation, identification, estimation (expectation–maximization/maximum likelihood and Bayesian), and goodness-of-fit. Its opening chapter, by Leo A. Goodman, frames latent class analysis as a tool for assessing whether observed relationships among manifest variables are real or spurious — see Goodman (2002), the source page covering that chapter in detail.

Key Claims

• Latent class analysis provides a unified framework for modeling associations among categorical variables through an unobserved discrete latent variable, encompassing measurement, typology, and causal-structure applications.
• Restricted latent class models can be as parsimonious as a null independence model while fitting substantially better, and they answer why a relationship exists rather than merely whether it is statistically significant.

Concepts Introduced or Extended

• Latent Class Model
• Mixture Model

Quotes

(Edited volume; see Goodman (2002) for the ingested Chapter 1 material.)

My Take

A stub for the edited volume that contains Goodman (2002) as its first chapter, created so the cross-reference from that chapter resolves. Only the Goodman chapter has been ingested in detail; the remaining chapters are not yet summarized here.