Matching IRT models to patient-reported outcomes constructs: the graded response and log-logistic models for scaling depression
type: Item
instance of: scholarly article
title: Matching IRT models to patient-reported outcomes constructs: the graded response and log-logistic models for scaling depression
zbMATH Open document ID: 1477.62349
author: Steven P. Reise
author: Han Du
author: Emily F. Wong
author: Anne S. Hubbard
author: Mark G. Haviland
published in: Psychometrika
publication date: 2022-01-14T00:00:00Z
Mathematics Subject Classification ID: 62P15
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 7457529
zbMATH Keywords: graded response model
zbMATH Keywords: log-logistic model
zbMATH Keywords: IRT model assumptions
describes a project that uses: mstR
describes a project that uses: catR
describes a project that uses: mirt
MaRDI profile type: Publication
full work available at URL: s11336-021-09802-0
OpenAlex ID: W3197805355
cites work: Measurement of learning and mental abilities
cites work: Q4315010
cites work: The heteroscedastic graded response model with a skewed latent trait: testing statistical and substantive hypotheses related to skewed item category functions
cites work: Estimating latent distributions
cites work: On the relationship between item response theory and factor analysis of discretized variables
cites work: Item response theory with estimation of the latent population distribution using spline-based densities
DOI: 10.1007/S11336-021-09802-0
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description: scientific article; zbMATH DE number 7457529