A new method for detecting differential item functioning in the Rasch model
Carolin Strobl (),
Julia Kopf () and
Achim Zeileis ()
Working Papers from Faculty of Economics and Statistics, University of Innsbruck
Differential item functioning (DIF) can lead to an unfair advantage or disadvantage for certain subgroups in educational and psychological testing. Therefore, a variety of statistical methods has been suggested for detecting DIF in the Rasch model. Most of these methods are designed for the comparison of pre-specified focal and reference groups, such as males and females. Latent class approaches, on the other hand, allow to detect previously unknown groups exhibiting DIF. However, this approach provides no straightforward interpretation of the groups with respect to person characteristics. Here we propose a new method for DIF detection based on model-based recursive partitioning that can be considered as a compromise between those two extremes. With this approach it is possible to detect groups of subjects exhibiting DIF, which are not prespecified, but result from combinations of observed ovariates. These groups are directly interpretable and can thus help understand the psychological sources of DIF. The statistical background and construction of the new method is first introduced by means of an instructive example, and then applied to data from a general knowledge quiz and a teaching evaluation.
Keywords: item response theory; IRT; Rasch model; di erential item functioning; DIF; structural change; multidimensionality. (search for similar items in EconPapers)
JEL-codes: C25 C29 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:inn:wpaper:2011-01
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