Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Análisis Factorial Exploratorio Bayesiano (BEFA)× | Análisis Factorial Confirmatorio (AFC)× | |
|---|---|---|
| Campo | Psicometría | Psicometría |
| Familia | Latent structure | Latent structure |
| Año de origen≠ | 2004 (Bayesian formulation); factor analysis roots: 1904 | 1969 |
| Autor original≠ | Lopes & West (seminal Bayesian treatment); roots in classical factor analysis (Spearman, 1904) | Karl Gustav Jöreskog |
| Tipo≠ | Probabilistic latent variable model | Hypothesis-testing latent variable model |
| Fuente seminal≠ | Lopes, H. F. & West, M. (2004). Bayesian model assessment in factor analysis. Statistica Sinica, 14(1), 41–67. link ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias | Bayesian factor analysis, BEFA, Bayesian common factor model, probabilistic factor analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Relacionados | 4 | 4 |
| Resumen≠ | Bayesian exploratory factor analysis applies a full probabilistic framework to the common factor model. By placing prior distributions over factor loadings and unique variances, it yields posterior distributions rather than point estimates, quantifies uncertainty around every loading, and can treat the number of factors as an unknown to be inferred from data. | 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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