Overview of Structural Equation Models and Recent Extensions

Abstract

This chapter gives an overview of structural equation models (SEMs) and describes some of the recent work that has shown how to incorporate multilevel models, mixture models, item response theory, and sample design into the SEM framework. It discusses two general approaches to multilevel SEM. The author refers to the first approach as the between-and-within specification and the second approach as the random-effects-as-factors specification. The chapter also discusses an extension for SEMs (and factor analysis) that permits the estimation of both continuous latent factors and discrete latent classes in the same model. It describes SEM models for categorical variables and their close relationship to item response theory models. The chapter presents the specific estimation problems for SEMs and some of the modeling techniques and estimation corrections that can be employed for proper inference when analyzing samples with nesting and unequal probabilities of selection. Controlled Vocabulary Terms Categorical variables; factor analysis; hierarchical linear model; mixture model

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 33 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.