Literature DB >> 34342818

Commentary: Matching IRT Models to PRO Constructs- Modeling Alternatives, and Some Thoughts on What Makes a Model Different.

Matthias von Davier1.   

Abstract

This commentary is an attempt to present some additional alternatives to the suggestions made by Reise et al. (2021). IRT models as they are used for patient-reported outcome (PRO) scales may not be fully satisfactory when used with commonly made assumptions. The suggested change to an alternative parameterization is critically reflected with the intent to initiate discussion around more comprehensive alternatives that allow for more complex latent structures having the potential to be more appropriate for PRO scales as they are applied to diverse populations.
© 2021. The Psychometric Society.

Entities:  

Keywords:  classification methods for clinical data; discrete latent trait models; item response theory; model equivalencies

Year:  2021        PMID: 34342818     DOI: 10.1007/s11336-021-09790-1

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  6 in total

1.  A conceptual and psychometric framework for distinguishing categories and dimensions.

Authors:  Paul De Boeck; Mark Wilson; G Scott Acton
Journal:  Psychol Rev       Date:  2005-01       Impact factor: 8.934

2.  The structure of posttraumatic stress disorder: latent class analysis in 2 community samples.

Authors:  Naomi Breslau; Beth A Reboussin; James C Anthony; Carla L Storr
Journal:  Arch Gen Psychiatry       Date:  2005-12

3.  Latent Class Analysis of DSM-5 Alcohol Use Disorder Criteria Among Heavy-Drinking College Students.

Authors:  Dipali Venkataraman Rinker; Clayton Neighbors
Journal:  J Subst Abuse Treat       Date:  2015-05-16

4.  A latent class analysis of DSM-IV criteria for pathological gambling: Results from the National Epidemiologic Survey on Alcohol and Related Conditions.

Authors:  Natacha Carragher; Lachlan A McWilliams
Journal:  Psychiatry Res       Date:  2011-01-17       Impact factor: 3.222

5.  Latent variable mixture models to test for differential item functioning: a population-based analysis.

Authors:  Xiuyun Wu; Richard Sawatzky; Wilma Hopman; Nancy Mayo; Tolulope T Sajobi; Juxin Liu; Jerilynn Prior; Alexandra Papaioannou; Robert G Josse; Tanveer Towheed; K Shawn Davison; Lisa M Lix
Journal:  Health Qual Life Outcomes       Date:  2017-05-15       Impact factor: 3.186

6.  A study of alternative approaches to non-normal latent trait distributions in item response theory models used for health outcome measurement.

Authors:  Niels Smits; Oğuzhan Öğreden; Mauricio Garnier-Villarreal; Caroline B Terwee; R Philip Chalmers
Journal:  Stat Methods Med Res       Date:  2020-03-11       Impact factor: 3.021

  6 in total

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