Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis

The data and code for this research are available at https://bit.ly/3xrP3Rq (accessed on 17 July 2024)

Detalhes bibliográficos
Autores: Ramírez, Eduar S, Jiménez Henríquez, Marcos José, Rosa Franco, Víthor, Alvarado Izquierdo, Jesús María
Formato: artículo
Fecha de publicación:2024
País:España
Recursos:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/720207
Acesso em linha:http://hdl.handle.net/10486/720207
https://dx.doi.org/10.3390/jintelligence12070067
Access Level:acceso abierto
Palavra-chave:analogical reasoning
response processes
multicomponent analysis
LLTM
MLTM-D
GMLTM-D
Psicología
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spelling Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for DiagnosisRamírez, Eduar SJiménez Henríquez, Marcos JoséRosa Franco, VíthorAlvarado Izquierdo, Jesús Maríaanalogical reasoningresponse processesmulticomponent analysisLLTMMLTM-DGMLTM-DPsicologíaThe data and code for this research are available at https://bit.ly/3xrP3Rq (accessed on 17 July 2024)Research on analogical reasoning has facilitated the understanding of response processes such as pattern identification and creative problem solving, emerging as an intelligence predictor. While analogical tests traditionally combine various composition rules for item generation, current statistical models like the Logistic Latent Trait Model (LLTM) and Embretson’s Multicomponent Latent Trait Model for Diagnosis (MLTM-D) face limitations in handling the inherent complexity of these processes, resulting in suboptimal model fit and interpretation. The primary aim of this research was to extend Embretson’s MLTM-D to encompass complex multidimensional models that allow the estimation of item parameters. Concretely, we developed a three-parameter (3PL) version of the MLTM-D that provides more informative interpretations of participant response processes. We developed the Generalized Multicomponent Latent Trait Model for Diagnosis (GMLTM-D), which is a statistical model that extends Embretson’s multicomponent model to explore complex analogical theories. The GMLTM-D was compared with LLTM and MLTM-D using data from a previous study of a figural analogical reasoning test composed of 27 items based on five composition rules: figure rotation, trapezoidal rotation, reflection, segment subtraction, and point movement. Additionally, we provide an R package (GMLTM) for conducting Bayesian estimation of the models mentioned. The GMLTM-D more accurately replicated the observed data compared to the Bayesian versions of LLTM and MLTM-D, demonstrating a better model fit and superior predictive accuracy. Therefore, the GMLTM-D is a reliable model for analyzing analogical reasoning data and calibrating intelligence tests. The GMLTM-D embraces the complexity of real data and enhances the understanding of examinees’ response processesGrant PID2022-136905OB-C22 funded by MCIN/AEI/ 10.13039/501100011033 Ministry of Science, Innovation and Universities (Spain)MDPIDepartamento de Psicología Social y MetodologíaFacultad de Psicología20242024-07-01research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/720207https://dx.doi.org/10.3390/jintelligence12070067reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7202072026-06-23T12:46:27Z
dc.title.none.fl_str_mv Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
title Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
spellingShingle Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
Ramírez, Eduar S
analogical reasoning
response processes
multicomponent analysis
LLTM
MLTM-D
GMLTM-D
Psicología
title_short Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
title_full Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
title_fullStr Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
title_full_unstemmed Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
title_sort Delving into the Complexity of Analogical Reasoning: A Detailed Exploration with the Generalized Multicomponent Latent Trait Model for Diagnosis
dc.creator.none.fl_str_mv Ramírez, Eduar S
Jiménez Henríquez, Marcos José
Rosa Franco, Víthor
Alvarado Izquierdo, Jesús María
author Ramírez, Eduar S
author_facet Ramírez, Eduar S
Jiménez Henríquez, Marcos José
Rosa Franco, Víthor
Alvarado Izquierdo, Jesús María
author_role author
author2 Jiménez Henríquez, Marcos José
Rosa Franco, Víthor
Alvarado Izquierdo, Jesús María
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Psicología Social y Metodología
Facultad de Psicología
dc.subject.none.fl_str_mv analogical reasoning
response processes
multicomponent analysis
LLTM
MLTM-D
GMLTM-D
Psicología
topic analogical reasoning
response processes
multicomponent analysis
LLTM
MLTM-D
GMLTM-D
Psicología
description The data and code for this research are available at https://bit.ly/3xrP3Rq (accessed on 17 July 2024)
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-07-01
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/720207
https://dx.doi.org/10.3390/jintelligence12070067
url http://hdl.handle.net/10486/720207
https://dx.doi.org/10.3390/jintelligence12070067
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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