Title: Differential Item Functioning with Item Focused Trees

Authors: Gerhard Tutz, Moritz Berger

Affiliation: Ludwig Maximilians University Munich

Abstract: A new method for the identification of differential item
functioning (DIF) by using recursive partitioning techniques is proposed.
We assume an extension of the Rasch model that allows for DIF being induced
by an arbitrary number of covariates for each item.  Recursive partitioning
on the item level results in one tree for each item and leads to
simultaneous selection of items and variables that induce DIF. For each
item it is possible to detect groups of subjects with different item
difficulties, defined by combinations of characteristics that are not
pre-specified.  An algorithm is proposed that is based on permutation
tests.  Various simulation studies, including the comparison with
traditional approaches to identify items with DIF, show the applicability
and the competitive performance of the method.  Two applications illustrate
the usefulness and the advantages of the new method.