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ERIC Number: EJ928373
Record Type: Journal
Publication Date: 2010
Pages: 26
Abstractor: As Provided
Reference Count: 48
ISSN: ISSN-0022-0655
RIM: A Random Item Mixture Model to Detect Differential Item Functioning
Frederickx, Sofie; Tuerlinckx, Francis; De Boeck, Paul; Magis, David
Journal of Educational Measurement, v47 n4 p432-457 Win 2010
In this paper we present a new methodology for detecting differential 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 difference between the DIF class and the non-DIF class is that the item difficulties in the DIF class may differ 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 data set.
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A