Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Desarrollo de escalas bayesianas× | Análisis Factorial Confirmatorio (AFC)× | |
|---|---|---|
| Campo | Psicometría | Psicometría |
| Familia | Latent structure | Latent structure |
| Año de origen≠ | 1990s–2000s | 1969 |
| Autor original≠ | Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues | Karl Gustav Jöreskog |
| Tipo≠ | Bayesian probabilistic scale construction | Hypothesis-testing latent variable model |
| Fuente seminal≠ | De Ayala, R. J. (2009). The Theory and Practice of Item Response Theory. Guilford Press. ISBN: 978-1593858698 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias | Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | Bayesian scale development applies Bayesian statistical inference to the construction and evaluation of psychometric scales. Rather than relying on single point estimates of item and person parameters, it produces full posterior distributions that quantify uncertainty, incorporate prior knowledge, and support principled decisions about item retention, reliability, and validity in small or complex samples. | 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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