Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Diferenciālā vienumu funkcionēšana (DVF)× | Apstiprinošā faktoru analīze (AFA)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1970s–1993 | 1969 |
| Autors≠ | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer | Karl Gustav Jöreskog |
| Tips≠ | Item-level bias detection | Hypothesis-testing latent variable model |
| Pirmavots≠ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Citi nosaukumi | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development. | 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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