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Item-Specific Factors in IRTree Models: When They Matter and When They Don’t

Lyu et al. (Psychometrika, 2023) demonstrated that item-specific factors can cause spurious effects on the structural parameters of IRTree models for multiple nested response processes per item. Here, we discuss some boundary conditions and argue that person selection effects on item parameters are...

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Detalles Bibliográficos
Autores principales: Meiser, Thorsten, Reiber, Fabiola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444655/
https://www.ncbi.nlm.nih.gov/pubmed/37326912
http://dx.doi.org/10.1007/s11336-023-09916-7
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author Meiser, Thorsten
Reiber, Fabiola
author_facet Meiser, Thorsten
Reiber, Fabiola
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description Lyu et al. (Psychometrika, 2023) demonstrated that item-specific factors can cause spurious effects on the structural parameters of IRTree models for multiple nested response processes per item. Here, we discuss some boundary conditions and argue that person selection effects on item parameters are not unique to item-specific factors and that the effects presented by Lyu et al. (Psychometrika, 2023) may not generalize to the family of IRTree models as a whole. We conclude with the recommendation that IRTree model specification should be guided by theoretical considerations, rather than driven by data, in order to avoid misinterpretations of parameter differences.
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spelling pubmed-104446552023-08-24 Item-Specific Factors in IRTree Models: When They Matter and When They Don’t Meiser, Thorsten Reiber, Fabiola Psychometrika Theory & Methods Lyu et al. (Psychometrika, 2023) demonstrated that item-specific factors can cause spurious effects on the structural parameters of IRTree models for multiple nested response processes per item. Here, we discuss some boundary conditions and argue that person selection effects on item parameters are not unique to item-specific factors and that the effects presented by Lyu et al. (Psychometrika, 2023) may not generalize to the family of IRTree models as a whole. We conclude with the recommendation that IRTree model specification should be guided by theoretical considerations, rather than driven by data, in order to avoid misinterpretations of parameter differences. Springer US 2023-06-16 2023 /pmc/articles/PMC10444655/ /pubmed/37326912 http://dx.doi.org/10.1007/s11336-023-09916-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Theory & Methods
Meiser, Thorsten
Reiber, Fabiola
Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title_full Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title_fullStr Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title_full_unstemmed Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title_short Item-Specific Factors in IRTree Models: When They Matter and When They Don’t
title_sort item-specific factors in irtree models: when they matter and when they don’t
topic Theory & Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444655/
https://www.ncbi.nlm.nih.gov/pubmed/37326912
http://dx.doi.org/10.1007/s11336-023-09916-7
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