Salīdzināt metodes

	Lineārā diskriminantā analīze	Apstiprinošā faktoru analīze (AFA)
Nozare	Statistika	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1936	1969
Autors	Ronald A. Fisher	Karl Gustav Jöreskog
Tips	Supervised classification and dimension reduction	Hypothesis-testing latent variable model
Pirmavots	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.
Citi nosaukumi	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis	CFA, confirmatory FA, measurement model, restricted factor analysis
Saistītās	4	4
Kopsavilkums	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.