Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Teoria Răspunsului la Item în Grupuri Multiple (MG-IRT)× | Analiza factoriala confirmatorie (CFA)× | |
|---|---|---|
| Domeniu | Psihometrie | Psihometrie |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 1990s | 1969 |
| Autorul original≠ | Multiple contributors; formalized by Birnbaum (1968) for IRT; multi-group extensions developed through 1980s–1990s | Karl Gustav Jöreskog |
| Tip≠ | Latent trait / measurement invariance | Hypothesis-testing latent variable model |
| Sursa seminală≠ | Embretson, S. E. & Reise, S. P. (2000). Item Response Theory for Psychologists. Lawrence Erlbaum Associates. ISBN: 978-0805828191 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Denumiri alternative | MG-IRT, multiple-group IRT, multi-group latent trait model, IRT across groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Înrudite≠ | 6 | 4 |
| Rezumat≠ | Multi-group item response theory fits IRT models simultaneously across two or more defined groups — such as males and females, or different cultural samples — to determine whether item parameters are invariant across those groups. It is the primary IRT-based framework for testing measurement equivalence and detecting differential item functioning (DIF) at the model level. | 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. |
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