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

Autor/inn/en	Kopf, Julia; Zeileis, Achim; Strobl, Carolin
Titel	Anchor selection strategies for DIF analysis: Review, assessment, and new approaches.
Quelle	In: Educational and psychological measurement, 75 (2015) 1, S. 22-56Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Beigaben	Literaturangaben
Zusatzinformation	Forschungsdaten, Studiendetails und Erhebungsinstrumente
Sprache	englisch
Dokumenttyp	online; gedruckt; Zeitschriftenaufsatz
ISSN	0013-1644; 1552-3888
DOI	10.1177/0013164414529792
Schlagwörter	Rasch-Modell; Bildungsforschung; Itemanalyse; Testtheorie; Messverfahren; Statistische Methode
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. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2015/4