Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzgrupu vienumu atbildes teorija (MG-IRT)× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990s | 1969 |
| Autors≠ | Multiple contributors; formalized by Birnbaum (1968) for IRT; multi-group extensions developed through 1980s–1990s | Karl Gustav Jöreskog |
| Tips≠ | Latent trait / measurement invariance | Hypothesis-testing latent variable model |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | MG-IRT, multiple-group IRT, multi-group latent trait model, IRT across groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | 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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