Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Datorizētās adaptīvās testēšanas mērījumu invariancē× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1990s–2000s | 1969 |
| Autors≠ | Building on Meredith (1993) for invariance and Lord (1980) for adaptive testing | Karl Gustav Jöreskog |
| Tips≠ | Measurement equivalence testing in adaptive testing contexts | Hypothesis-testing latent variable model |
| Pirmavots≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-0805864946 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Citi nosaukumi | CAT measurement invariance, adaptive test invariance, CAT MI, measurement equivalence in CAT | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | Computerized adaptive test measurement invariance evaluates whether a CAT instrument measures the same latent construct with the same psychometric properties across different groups (e.g., gender, language, clinical vs. community) or time points. It combines IRT-based adaptive test frameworks with measurement equivalence testing to ensure fair and comparable score interpretation. | 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. |
| ScholarGateDatu kopa ↗ |
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