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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
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Matching IRT Models to Patient-Reported Outcomes Constructs: The Graded Response and Log-Logistic Models for Scaling

Steven P Reise1, Han Du2, Emily F Wong2

  • 1Department of Psychology, University of California, Los Angeles, Los Angeles, USA. reise@psych.ucla.edu.

Psychometrika
|August 31, 2021
PubMed
Summary

Item response theory (IRT) models are used for patient-reported outcomes (PRO). A log-logistic model may better represent depression than traditional IRT models, impacting psychometric analysis.

Keywords:
IRT model assumptionsgraded response modellog-logistic model

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Area of Science:

  • Psychometrics
  • Health Outcomes Research

Background:

  • Item response theory (IRT) is widely applied beyond cognitive testing, notably in patient-reported outcomes (PRO).
  • Traditional IRT models, like the graded response model, are often used for PRO, despite differences from cognitive constructs.
  • These differences can pose challenges for traditional IRT model fitting.

Purpose of the Study:

  • To review differences between cognitive and PRO constructs affecting IRT model application.
  • To compare the traditional graded response model with an alternative log-logistic model for PRO data.
  • To explore model appropriateness beyond statistical fit, integrating theory and construct-specific research.

Main Methods:

  • Review of theoretical differences between cognitive and PRO constructs.
  • Application of the graded response model and the log-logistic model to depression measure data.
  • Analysis of depression data from the Patient-Reported Outcomes Measurement Information System (PROMIS) project.

Main Results:

  • The log-logistic model may align better with depression as a unipolar construct compared to the graded response model.
  • Different IRT models can yield divergent conclusions regarding instrument psychometrics and individual differences.
  • Model selection for PRO requires considering construct theory, not solely fit indices.

Conclusions:

  • The choice of IRT model for PRO measures, such as depression, has significant psychometric implications.
  • The log-logistic model offers a potentially more suitable framework for unipolar constructs like depression.
  • Integrating psychometric analysis with construct-specific theory is crucial for appropriate model selection in PRO research.