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| Polytomous Measurement Invariance× | Diferenciālā vienumu funkcionēšana (DVF)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 2000–2004 | 1970s–1993 |
| Autors≠ | Roger E. Millsap, Robert J. Vandenberg | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Tips≠ | Multi-group confirmatory test | Item-level bias detection |
| Pirmavots≠ | Millsap, R. E. & Kwok, O.-M. (2004). Evaluating the impact of partial factor loading and intercept invariance on selection utility. Psychological Methods, 9(2), 200–215. link ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Citi nosaukumi | PMI, ordinal measurement invariance, polytomous factorial invariance, polytomous multi-group measurement invariance | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Polytomous measurement invariance testing evaluates whether a scale with ordered categorical (polytomous) response options — such as Likert-type items — measures the same latent construct in the same way across two or more groups. It extends classical multi-group CFA invariance testing to properly account for the ordinal nature of item responses, ensuring that group comparisons of latent means or factor structures are substantively valid. | 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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