The Generalized Thurstonian Unfolding Model (GTUM): Advancing the Modeling of Forced-Choice Data

Bo Zhang, Naidan Tu, Lawrence Angrave, Susu Zhang, Tianjun Sun, Louis Tay, Jian Li

Research output: Contribution to journalArticlepeer-review

Abstract

Forced-choice (FC) measurement has become increasingly popular due to its robustness to various response biases and reduced susceptibility to faking. Although several current Item Response Theory (IRT) models can extract normative person scores from FC responses, each has its limitations. This study proposes the Generalized Thurstonian Unfolding Model (GTUM) as a more flexible IRT model for FC measures to overcome these limitations. The GTUM (1) adheres to the unfolding response process, (2) accommodates FC scales of any block size, and (3) manages both dichotomous and graded responses. Monte Carlo simulation studies consistently demonstrated that the GTUM exhibited good statistical properties under most realistic conditions. Particularly noteworthy findings include (1) the GTUM's ability to handle FC scales with or without intermediate statements, (2) the consistently superior performance of graded responses over dichotomous responses in person score recovery, and (3) the sufficiency of 10 mixed pairs to ensure robust psychometric performance. Two empirical examples, one with 1,033 responses to a static version of the Tailored Adaptative Personality Assessment System and the other with 759 responses to a graded version of the Forced-Choice Five-Factor Markers, demonstrated the feasibility of the GTUM to handle different types of FC scales. To aid in the practical use of the GTUM, we also developed the R package “fcscoring”.

Original languageEnglish (US)
JournalOrganizational Research Methods
DOIs
StateAccepted/In press - 2023

Keywords

  • GTUM
  • Item Response Theory
  • forced-choice
  • unfolding response process

ASJC Scopus subject areas

  • General Decision Sciences
  • Strategy and Management
  • Management of Technology and Innovation

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