Salīdzināt metodes
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| Ordinālās mērīšanas invariances testēšana× | Diferenciālā vienumu funkcionēšana (DVF)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1984–2011 | 1970s–1993 |
| Autors≠ | Roger Millsap; Bengt Muthén | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Tips≠ | Multi-group model comparison | Item-level bias detection |
| Pirmavots≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Citi nosaukumi | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal data are treated as continuous. | 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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