flexMIRT: A Flexible Modeling Package for Multidimensional Item Response Models

Seungwon Chung, Carrie Houts

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Advanced modeling of item response data through the item response theory (IRT) or item factor analysis frameworks is becoming increasingly popular. In the social and behavioral sciences, the underlying structure of tests/assessments is often multidimensional (i.e., more than 1 latent variable/construct is represented in the items). This review provides an introduction and overview of flexMIRT 3.5, a commercially available statistical software program for the analysis of item response data that was developed specifically for fitting such complex models. Three models are used as motivating examples: (a) a bifactor model, (b) a multidimensional IRT (MIRT) model with correlated factors and (c) a diagnostic classification model with testlet structure. Discussion regarding flexMIRT input syntax and output files is provided and the topics of model fit evaluation, limited-information fit statistics in particular, and specifics of more recently introduced estimation methods and models are also covered.

Original languageEnglish (US)
Pages (from-to)40-54
Number of pages15
JournalMeasurement
Volume18
Issue number1
DOIs
StatePublished - Jan 2 2020

Bibliographical note

Publisher Copyright:
© 2020, © 2020 Taylor & Francis Group, LLC.

Keywords

  • MH-RM
  • Multidimensional IRT
  • diagnostic classification model
  • flexMIRT
  • limited-information fit statistics

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