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| Validité de construit polytomique× | Fonctionnement différentiel des items (FDI)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1992–2000 | 1970s–1993 |
| Auteur d'origine≠ | Building on Messick (1989) and IRT extensions by Masters, Muraki, and Samejima | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Type≠ | Psychometric validity framework | Item-level bias detection |
| Source fondatrice≠ | Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176. DOI ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Alias | polytomous item construct validity, ordered-category construct validity, polytomous measurement validity, multi-category scale validity | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Polytomous construct validity refers to the evaluation of whether a scale composed of ordered, multi-category items (e.g., Likert or rating-scale items) genuinely measures the intended latent construct. It extends classical validity frameworks to polytomous measurement models — such as the Graded Response Model or Generalized Partial Credit Model — ensuring that ordered response categories function as designed and that the resulting scores reflect the target construct. | 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. |
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