Reference : RIM: A random item mixture model to detect differential item functioning.
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Mathematics
RIM: A random item mixture model to detect differential item functioning.
[fr] RIM: un modèle de mixture à items aléatoires pour détecter le fonctionnement différentiel d'items
Frederickx, Sofie [ > > ]
Tuerlinckx, Francis [ > > ]
De Boeck, Paul [ > > ]
Magis, David mailto [Université de Liège - ULg > Département de mathématique > Statistique mathématique >]
Journal of Educational Measurement
Blackwell Publishing
Yes (verified by ORBi)
[en] Differential item functioning ; IRT ; Bayesian analysis
[en] In this article we present a new methodology for detecting Di erential Item Functioning (DIF). We
introduce a DIF model, called the Random Item Mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is assumed for the item difficulties such that the items may belong to one of two classes: a DIF or a non-DIF class. The crucial di fference between the DIF class and the non-DIF class is that the item difficulties in the DIF class may di ffer according to the observed person groups while they are equal across the person groups for the items from the non-DIF class. Statistical inference for the RIM is carried out in a Bayesian framework. The performance of the RIM is evaluated using a simulation study in which it is compared with traditional procedures, like the Likelihood Ratio test, the Mantel-Haenszel procedure and the standardized p-DIF procedure. In this comparison, the RIM performs better than the other methods. Finally, the usefulness of the model is also demonstrated on a real life dataset.

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Journal of Educational Measurement 47 (2010),432--457.pdfPublisher postprint461.13 kBRequest copy

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