Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis discriminante× | Análisis Factorial Confirmatorio (AFC)× | |
|---|---|---|
| Campo≠ | Estadística | Psicometría |
| Familia | Latent structure | Latent structure |
| Año de origen≠ | 1936 | 1969 |
| Autor original≠ | Ronald A. Fisher | Karl Gustav Jöreskog |
| Tipo≠ | Supervised classification and dimension reduction | Hypothesis-testing latent variable model |
| Fuente seminal≠ | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Relacionados | 4 | 4 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
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