Abstract
A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel—Haenszel and logistic regression analysis. A nonparametric classification rule is examined through simulation and real data, and Type I error and power are compared with equivalent Mantel—Haenszel, logistic regression, and discriminant analyses.
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