Detection of Uniform and Nonuniform Differential Item Functioning by Item Focussed Trees

Berger, Moritz und Tutz, Gerhard (2016): Detection of Uniform and Nonuniform Differential Item Functioning by Item Focussed Trees. In: Journal of Educational and Behavioral Statistics, Bd. 41, Nr. 6: S. 559-592

Abstract

Detection of differential item functioning (DIF) by use of the logistic modeling approach has a long tradition. One big advantage of the approach is that it can be used to investigate nonuniform (NUDIF) as well as uniform DIF (UDIF). The classical approach allows one to detect DIF by distinguishing between multiple groups. We propose an alternative method that is a combination of recursive partitioning methods (or trees) and logistic regression methodology to detect UDIF and NUDIF in a nonparametric way. The output of the method are trees that visualize in a simple way the structure of DIF in an item showing which variables are interacting in which way when generating DIF. In addition, we consider a logistic regression method, in which DIF can be induced by a vector of covariates, which may include categorical but also continuous covariates. The methods are investigated in simulation studies and illustrated by two applications.

• Dokumententyp: Zeitschriftenartikel
• Publikationsform: Publisher's Version
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Lehrstühle/Arbeitsgruppen > Seminar für angewandte Stochastik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• ISSN: 1935-1054
• Allianz-/Nationallizenz: Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
• Sprache: Englisch