Salīdzināt metodes

	Robustā atšķirīgā vienumu funkcionēšana (Robust DIF)	Diferenciālā vienumu funkcionēšana (DVF)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1990s–2000s	1970s–1993
Autors	Building on DIF work by Cleary & Hilton (1968) and Mantel-Haenszel by Holland & Thayer (1988); robust extensions developed through 1990s–2000s	William H. Angoff and colleagues (ETS); systematized by Holland & Wainer
Tips	Item bias / fairness analysis	Item-level bias detection
Pirmavots	Magis, D., Beland, S., Tuerlinckx, F., & De Boeck, P. (2011). A general framework and an R package for the detection of dichotomous differential item functioning. Behavior Research Methods, 43(3), 847–862.	Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589
Citi nosaukumi	Robust DIF, outlier-resistant DIF detection, robust item bias analysis, DIF with robust estimation	DIF, item bias analysis, measurement non-equivalence, item-level measurement bias
Saistītās	6	5
Kopsavilkums	Robust differential item functioning analysis detects items that behave differently across demographic groups after matching respondents on the underlying trait, while protecting the procedure against distortion by outliers, model misfit, or contaminated anchor items. It is applied in educational testing, clinical assessment, and survey research to ensure that a scale measures the same construct equally fairly for all groups.	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.