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A dual process item response theory model for polytomous multidimensional forced-choice items.

Xuelan Qiu1, Jimmy de la Torre2

  • 1Institute for Learning Sciences & Teacher Education, Australian Catholic University, Brisbane, Queensland, Australia.

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Summary
This summary is machine-generated.

This study introduces a new item response theory (IRT) model for polytomous multidimensional forced-choice (MFC) items, enhancing the assessment of non-cognitive traits like personality and interests.

Keywords:
cognitive model of choiceitem response theorymultidimensional forced choicepsychological differentiation

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Area of Science:

  • Psychometrics
  • Psychological Measurement
  • Item Response Theory

Background:

  • Multidimensional forced-choice (MFC) items are valuable for assessing non-cognitive traits due to their resistance to response bias.
  • Existing item response theory (IRT) models primarily focus on binary MFC items, limiting their application to more informative polytomous formats.
  • Polytomous MFC items, with more than two categories, offer greater informational content than binary items.

Purpose of the Study:

  • To develop a novel IRT model specifically for polytomous MFC items.
  • To address the limitations of existing IRT models for binary MFC items.
  • To account for the ipsative nature of polytomous MFC items and assess individual trait differentiation.

Main Methods:

  • Developed a new IRT model for polytomous MFC items, integrating a cognitive model of choice.
  • Conducted simulation studies to evaluate parameter recovery using existing software.
  • Applied the model to an empirical example of a career interest test with four-category MFC items.

Main Results:

  • The new IRT model demonstrated good recovery of both statement and person parameters with sufficient sample sizes.
  • Parameter estimation accuracy improved with more complete statement linking.
  • The model successfully assessed individual differentiation in interests, values, and emotions.

Conclusions:

  • The proposed IRT model offers a promising approach for analyzing polytomous MFC items.
  • The model facilitates the assessment and comparison of trait differentiation between individuals.
  • Further validation is needed for certain aspects, such as the nature of person parameters.