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Detection of differential item functioning by use of the logistic modellingapproach has a long tradition. One big advantage of the approach is that it canbe used to investigate non-uniform DIF as well as uniform DIF. The classicalapproach allows to detect DIF by distinguishing between multiple groups. Wepropose an alternative method that is a combination of recursive partitioningmethods (or trees) and logistic regression methodology to detect uniform andnon-uniform DIF in a nonparametric way. The output of the method are trees thatvisualize in a simple way the structure of DIF in an item showing whichvariables are interacting in which way when generating DIF. In addition weconsider a logistic regression method in which DIF can by induced by a vectorof covariates, which may include categorical but also continuous covariates.The methods are investigated in simulation studies and illustrated by twoapplications.

Detection of Uniform and Non-Uniform Differential Item Functioning by Item Focussed Trees