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| Διαφορική Λειτουργία Αντικειμένου (DIF)× | Επιβεβαιωτική Παραγοντική Ανάλυση Πολλαπλών Ομάδων (MG-CFA)× | |
|---|---|---|
| Πεδίο | Ψυχομετρία | Ψυχομετρία |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 1970s–1993 | 1971 |
| Δημιουργός≠ | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer | Karl Jöreskog |
| Τύπος≠ | Item-level bias detection | Measurement model / invariance test |
| Θεμελιώδης πηγή≠ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ |
| Εναλλακτικές ονομασίες | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Συναφείς≠ | 5 | 6 |
| Σύνοψη≠ | 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. | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. |
| ScholarGateΣύνολο δεδομένων ↗ |
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