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Editorial
Educational Measurement: Issues and Practice, Volume 44, Issue 1, Page 5-5, Spring 2025.
Module Abstract
Item response tree (IRTree) models, an item response modeling approach that incorporates a tree structure, have become a popular method for many applications in measurement. IRTree models characterize the underlying response processes using a decision tree structure, where the internal decision outcome at each node is parameterized with an item response theory (IRT) model. Such models provide a flexible way of investigating and modeling underlying response processes, which can be useful for examining sources of individual differences in measurement and addressing measurement issues that traditional IRT models cannot deal with. In this module, we discuss the conceptual framework of IRTree models and demonstrate examples of their applications in the context of both cognitive and noncognitive assessments. We also introduce some possible extensions of the model and provide a demonstration of an example data analysis in R.
