Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzgrupu atšķirīgās pozīcijas funkcionēšana (MG-DIF)× | Vienuma atbildes teorija (IRT)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1980s-1990s | 1952–1968 |
| Autors≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Tips≠ | Measurement bias detection | Probabilistic measurement model |
| Pirmavots≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Citi nosaukumi | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid score comparisons. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGateDatu kopa ↗ |
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