Exploratory bi-factor analysis with multiple general factors

Exploratory bi-factor analysis (EBFA) is a very popular approach to estimate models wherespecific factors are concomitant to a single, general dimension. However, the models typic-ally encountered in fields like personality, intelligence, and psychopathology involve morethan one general factor. To a...

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Detalles Bibliográficos
Autores: Jiménez Henríquez, Marcos José, García Garzon, Eduardo, Garrido, Luis Eduardo, Abad García, Francisco José
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/712974
Acceso en línea:http://hdl.handle.net/10486/712974
https://dx.doi.org/10.1080/00273171.2023.2189571
Access Level:acceso abierto
Palabra clave:Bi-factor analysis
exploratory factor analysis
hierarchical structures
target rotation
Psicología
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spelling Exploratory bi-factor analysis with multiple general factorsJiménez Henríquez, Marcos JoséGarcía Garzon, EduardoGarrido, Luis EduardoAbad García, Francisco JoséBi-factor analysisexploratory factor analysishierarchical structurestarget rotationPsicologíaExploratory bi-factor analysis (EBFA) is a very popular approach to estimate models wherespecific factors are concomitant to a single, general dimension. However, the models typic-ally encountered in fields like personality, intelligence, and psychopathology involve morethan one general factor. To address this circumstance, we developed an algorithm (GSLiD)based on partially specified targets to perform exploratory bi-factor analysis with multiplegeneral factors (EBFA-MGF). In EBFA-MGF, researchers do not need to conduct independentbi-factor analyses anymore because several bi-factor models are estimated simultaneously inan exploratory manner, guarding against biased estimates and model misspecification errorsdue to unexpected cross-loadings and factor correlations. The results from an exhaustiveMonte Carlo simulation manipulating nine variables of interest suggested that GSLiD outper-forms the Schmid-Leiman approximation and is robust to challenging conditions involvingcross-loadings and pure items of the general factors. Thereby, we supply an R package(bifactor) to make EBFA-MGF readily available for substantive research. Finally, we useGSLiD to assess the hierarchical structure of a reduced version of the Personality Inventoryfor DSM-5 Short Form (PID-5-SF)This research was supported by Grant PSI2017-85022-P (Ministerio de Ciencia, Innovación y Universidades, Spain) and the UAM IIC Chair Psychometric Models and ApplicationsTaylor & Francis groupDepartamento de Psicología Social y MetodologíaFacultad de Psicología20232023-01-01research articlehttp://purl.org/coar/resource_type/c_2df8fbb1AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/712974https://dx.doi.org/10.1080/00273171.2023.2189571reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7129742026-06-23T12:46:27Z
dc.title.none.fl_str_mv Exploratory bi-factor analysis with multiple general factors
title Exploratory bi-factor analysis with multiple general factors
spellingShingle Exploratory bi-factor analysis with multiple general factors
Jiménez Henríquez, Marcos José
Bi-factor analysis
exploratory factor analysis
hierarchical structures
target rotation
Psicología
title_short Exploratory bi-factor analysis with multiple general factors
title_full Exploratory bi-factor analysis with multiple general factors
title_fullStr Exploratory bi-factor analysis with multiple general factors
title_full_unstemmed Exploratory bi-factor analysis with multiple general factors
title_sort Exploratory bi-factor analysis with multiple general factors
dc.creator.none.fl_str_mv Jiménez Henríquez, Marcos José
García Garzon, Eduardo
Garrido, Luis Eduardo
Abad García, Francisco José
author Jiménez Henríquez, Marcos José
author_facet Jiménez Henríquez, Marcos José
García Garzon, Eduardo
Garrido, Luis Eduardo
Abad García, Francisco José
author_role author
author2 García Garzon, Eduardo
Garrido, Luis Eduardo
Abad García, Francisco José
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 Bi-factor analysis
exploratory factor analysis
hierarchical structures
target rotation
Psicología
topic Bi-factor analysis
exploratory factor analysis
hierarchical structures
target rotation
Psicología
description Exploratory bi-factor analysis (EBFA) is a very popular approach to estimate models wherespecific factors are concomitant to a single, general dimension. However, the models typic-ally encountered in fields like personality, intelligence, and psychopathology involve morethan one general factor. To address this circumstance, we developed an algorithm (GSLiD)based on partially specified targets to perform exploratory bi-factor analysis with multiplegeneral factors (EBFA-MGF). In EBFA-MGF, researchers do not need to conduct independentbi-factor analyses anymore because several bi-factor models are estimated simultaneously inan exploratory manner, guarding against biased estimates and model misspecification errorsdue to unexpected cross-loadings and factor correlations. The results from an exhaustiveMonte Carlo simulation manipulating nine variables of interest suggested that GSLiD outper-forms the Schmid-Leiman approximation and is robust to challenging conditions involvingcross-loadings and pure items of the general factors. Thereby, we supply an R package(bifactor) to make EBFA-MGF readily available for substantive research. Finally, we useGSLiD to assess the hierarchical structure of a reduced version of the Personality Inventoryfor DSM-5 Short Form (PID-5-SF)
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/712974
https://dx.doi.org/10.1080/00273171.2023.2189571
url http://hdl.handle.net/10486/712974
https://dx.doi.org/10.1080/00273171.2023.2189571
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-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/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-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis group
publisher.none.fl_str_mv Taylor & Francis group
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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