Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Teoria della Generalizzabilità (G-Theory)× | Confirmatory factor analysis× | |
|---|---|---|
| Campo | Psicometria | Psicometria |
| Famiglia | Latent structure | Latent structure |
| Anno di origine≠ | 1963–1972 | 1969 |
| Ideatore≠ | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam | Karl Gustav Jöreskog |
| Tipo≠ | Variance-components reliability model | Hypothesis-testing latent variable model |
| Fonte seminale≠ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias≠ | G-theory, G-study / D-study framework, variance components reliability | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Correlati | 4 | 4 |
| Sintesi≠ | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. | 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. |
| ScholarGateInsieme di dati ↗ |
|
|