2015/11/23 by Moritz Berger, Gerhard Tutz, Berger, Moritz +1
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Modeling Techniques #FOS: Computer and information sciences #Methodology (stat.ME) #Psychometric Methodologies and Testing #Statistical Methods and Applications
paper · pdf · doi:10.48550/arxiv.1511.07178
openalex publication_date 2015/11/23 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
Detection of differential item functioning by use of the logistic modelling approach has a long tradition. One big advantage of the approach is that it can be used to investigate non-uniform DIF as well as uniform DIF. The classical approach allows 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 uniform and non-uniform DIF 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 by 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.