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Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes

It is essential to control self-reported trait measurements for response style effects to ensure a valid interpretation of estimates. Traditional psychometric models facilitating such control consider item responses as the result of two kinds of response processes—based on the substantive trait, or...

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Autores principales: Merhof, Viola, Meiser, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656330/
https://www.ncbi.nlm.nih.gov/pubmed/36746887
http://dx.doi.org/10.1007/s11336-023-09901-0
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author Merhof, Viola
Meiser, Thorsten
author_facet Merhof, Viola
Meiser, Thorsten
author_sort Merhof, Viola
collection PubMed
description It is essential to control self-reported trait measurements for response style effects to ensure a valid interpretation of estimates. Traditional psychometric models facilitating such control consider item responses as the result of two kinds of response processes—based on the substantive trait, or based on response styles—and they assume that both of these processes have a constant influence across the items of a questionnaire. However, this homogeneity over items is not always given, for instance, if the respondents’ motivation declines throughout the questionnaire so that heuristic responding driven by response styles may gradually take over from cognitively effortful trait-based responding. The present study proposes two dynamic IRTree models, which account for systematic continuous changes and additional random fluctuations of response strategies, by defining item position-dependent trait and response style effects. Simulation analyses demonstrate that the proposed models accurately capture dynamic trajectories of response processes, as well as reliably detect the absence of dynamics, that is, identify constant response strategies. The continuous version of the dynamic model formalizes the underlying response strategies in a parsimonious way and is highly suitable as a cognitive model for investigating response strategy changes over items. The extended model with random fluctuations of strategies can adapt more closely to the item-specific effects of different response processes and thus is a well-fitting model with high flexibility. By using an empirical data set, the benefits of the proposed dynamic approaches over traditional IRTree models are illustrated under realistic conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11336-023-09901-0.
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spelling pubmed-106563302023-02-06 Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes Merhof, Viola Meiser, Thorsten Psychometrika Theory & Methods It is essential to control self-reported trait measurements for response style effects to ensure a valid interpretation of estimates. Traditional psychometric models facilitating such control consider item responses as the result of two kinds of response processes—based on the substantive trait, or based on response styles—and they assume that both of these processes have a constant influence across the items of a questionnaire. However, this homogeneity over items is not always given, for instance, if the respondents’ motivation declines throughout the questionnaire so that heuristic responding driven by response styles may gradually take over from cognitively effortful trait-based responding. The present study proposes two dynamic IRTree models, which account for systematic continuous changes and additional random fluctuations of response strategies, by defining item position-dependent trait and response style effects. Simulation analyses demonstrate that the proposed models accurately capture dynamic trajectories of response processes, as well as reliably detect the absence of dynamics, that is, identify constant response strategies. The continuous version of the dynamic model formalizes the underlying response strategies in a parsimonious way and is highly suitable as a cognitive model for investigating response strategy changes over items. The extended model with random fluctuations of strategies can adapt more closely to the item-specific effects of different response processes and thus is a well-fitting model with high flexibility. By using an empirical data set, the benefits of the proposed dynamic approaches over traditional IRTree models are illustrated under realistic conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11336-023-09901-0. Springer US 2023-02-06 2023 /pmc/articles/PMC10656330/ /pubmed/36746887 http://dx.doi.org/10.1007/s11336-023-09901-0 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
Merhof, Viola
Meiser, Thorsten
Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title_full Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title_fullStr Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title_full_unstemmed Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title_short Dynamic Response Strategies: Accounting for Response Process Heterogeneity in IRTree Decision Nodes
title_sort dynamic response strategies: accounting for response process heterogeneity in irtree decision nodes
topic Theory & Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656330/
https://www.ncbi.nlm.nih.gov/pubmed/36746887
http://dx.doi.org/10.1007/s11336-023-09901-0
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