Digital Module 37: Introduction to Item Response Tree (IRTree) Models

Nana Kim, Jiayi Deng, Yun Leng Wong

Research output: Contribution to journalEditorialpeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)109-110
Number of pages2
JournalEducational Measurement: Issues and Practice
Volume44
Issue number1
DOIs
StatePublished - Mar 1 2025

Bibliographical note

Publisher Copyright:
© 2025 by the National Council on Measurement in Education.

Keywords

  • internal decision process
  • item response theory
  • item response tree (IRTree) model
  • response process
  • response styles
  • test-taking behaviors
  • tree structure

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