Comparer des méthodes

	Analyse discriminante	Analyse Factorielle Confirmatoire (AFC)
Domaine	Statistique	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1936	1969
Auteur d'origine	Ronald A. Fisher	Karl Gustav Jöreskog
Type	Supervised classification and dimension reduction	Hypothesis-testing latent variable model
Source fondatrice	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	4	4
Résumé	Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.	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.