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Commentary: Matching IRT Models to PRO Constructs- Modeling Alternatives, and Some Thoughts on What Makes a Model
1Boston College, 194 Beacon Street, Chestnut Hill, MA, 02467, USA. vondavim@bc.edu.
Psychometrika
|August 3, 2021
Summary
This commentary explores alternatives to current Item Response Theory (IRT) models for patient-reported outcome (PRO) scales. It suggests more complex models may better suit diverse populations.
Area of Science:
- Psychometrics
- Health Outcomes Research
Background:
- Item Response Theory (IRT) models are commonly used for patient-reported outcome (PRO) scales.
- Existing IRT models and their assumptions may not be fully satisfactory for diverse populations.
- Reise et al. (2021) proposed suggestions for improving IRT models for PRO scales.
Purpose of the Study:
- To present additional alternatives to the suggestions made by Reise et al. (2021).
- To critically reflect on alternative parameterizations for IRT models.
- To initiate discussion on more comprehensive IRT alternatives for PRO scales.
Main Methods:
- Commentary and critical reflection on existing IRT models.
- Exploration of alternative parameterizations and latent structures.
- Discussion of applicability to diverse populations.
Main Results:
- Current IRT model assumptions may be inadequate for PRO scales.
- Alternative parameterizations warrant critical evaluation.
- More complex latent structures may offer improved appropriateness for PRO scales.
Conclusions:
- There is a need for more comprehensive IRT models for PRO scales.
- The proposed alternatives aim to better accommodate diverse populations.
- Further discussion is needed to refine IRT models for patient-reported outcomes.
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