A new method for detecting differential item functioning in the Rasch model
AbstractDifferential 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.
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Bibliographic InfoPaper provided by Faculty of Economics and Statistics, University of Innsbruck in its series Working Papers with number 2011-01.
Date of creation: Jan 2011
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item response theory; IRT; Rasch model; di erential item functioning; DIF; structural change; multidimensionality.;
Find related papers by JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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- Achim Zeileis & Kurt Hornik, 2007. "Generalized M-fluctuation tests for parameter instability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 488-508.
- Hannah Frick & Carolin Strobl & Friedrich Leisch & Achim Zeileis, 2011. "Flexible Rasch Mixture Models with Package psychomix," Working Papers 2011-21, Faculty of Economics and Statistics, University of Innsbruck.
- Ting Wang & Edgar C. Merkle & Achim Zeileis, 2013. "Score-Based Tests of Measurement Invariance: Use in Practice," Working Papers 2013-33, Faculty of Economics and Statistics, University of Innsbruck.
- Edgar C. Merkle & Jinyan Fan & Achim Zeileis, 2012. "Testing for Measurement Invariance with Respect to an Ordinal Variable," Working Papers 2012-24, Faculty of Economics and Statistics, University of Innsbruck.
- Edgar C. Merkle & Achim Zeileis, 2011. "Generalized Measurement Invariance Tests with Application to Factor Analysis," Working Papers 2011-09, Faculty of Economics and Statistics, University of Innsbruck.
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