Anchor selection strategies for DIF analysis: Review, assessment, and new approaches

Kopf, Julia; Zeileis, Achim und Strobl, Carolin (24. November 2013): Anchor selection strategies for DIF analysis: Review, assessment, and new approaches. Department of Statistics: Technical Reports, Nr. 150

Abstract

Differential item functioning (DIF) indicates the violation of the invariance assumption for instance in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g. for the reference and the focal group) is necessary. In the Rasch model, therefore, the same linear restriction is imposed in both groups. Items in the restriction are termed the anchor items. Ideally, these items are DIF-free to avoid artificially augmented false alarm rates. However, the question how DIF-free anchor items are selected appropriately is still a major challenge. Furthermore, various authors point out the lack of new anchor selection strategies and the lack of a comprehensive study especially for dichotomous IRT models. This article reviews existing anchor selection strategies that do not require any knowledge prior to DIF analysis, offers a straightforward notation and proposes three new anchor selection strategies. An extensive simulation study is conducted to compare the performance of the anchor selection strategies. The results show that an appropriate anchor selection is crucial for suitable item-wise DIF analysis. The newly suggested anchor selection strategies outperform the existing strategies and can reliably locate a suitable anchor when the sample sizes are large enough.

• Dokumententyp: Paper
• Keywords: Rasch model, differential item functioning (DIF), anchor selection, anchor class, uniform DIF, measurement invariance
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Technische Reports
• Themengebiete: 100 Philosophie und Psychologie > 150 Psychologie ; 300 Sozialwissenschaften > 310 Statistiken
• Sprache: Englisch