Comparer des méthodes

	Théorie de la généralisabilité (Théorie G)	Analyse Factorielle Confirmatoire (AFC)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1963–1972	1969
Auteur d'origine	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam	Karl Gustav Jöreskog
Type	Variance-components reliability model	Hypothesis-testing latent variable model
Source fondatrice	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	G-theory, G-study / D-study framework, variance components reliability	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	4	4
Résumé	Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.