Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators

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Bifactor models have gained increasing popularity in the literature concerned with personality, psychopathology and assessment. Empirical studies using bifactor analysis generally judge the estimated model using SEM model fit indices, which may lead to erroneous interpretations and conclusions. To a...

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Autores principales:	Flores-Kanter, Pablo Ezequiel, Dominguez-Lara, Sergio, Trógolo, Mario Alberto, Medrano, Leonardo Adrián
Formato:	Artículo revista
Lenguaje:	Español
Publicado:	Facultad de Psicología. Laboratorio de Evaluación Psicológica y Educativa (LEPE) 2018
Materias:	confirmatory factor analyses bifactor models PANAS complementary statistical fit indices
Acceso en línea:	https://revistas.unc.edu.ar/index.php/revaluar/article/view/22221
Aporte de:	Revistas de la UNC de Universidad Nacional de Córdoba

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spelling	I10-R10-article-222212021-06-06T22:13:15Z Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators Flores-Kanter, Pablo Ezequiel Dominguez-Lara, Sergio Trógolo, Mario Alberto Medrano, Leonardo Adrián confirmatory factor analyses bifactor models PANAS complementary statistical fit indices confirmatory factor analyses bifactor models PANAS complementary statistical fit indices Bifactor models have gained increasing popularity in the literature concerned with personality, psychopathology and assessment. Empirical studies using bifactor analysis generally judge the estimated model using SEM model fit indices, which may lead to erroneous interpretations and conclusions. To address this problem, several researchers have proposed multiple criteria to assess bifactor models, such as a) conceptual grounds, b) overall model fit indices, and c) specific bifactor model indicators. In this article, we provide a brief summary of these criteria. An example using data gathered from a recently published research article is also provided to show how taking into account all criteria, rather than solely SEM model fit indices, may prevent researchers from drawing wrong conclusions. Bifactor models have gained increasing popularity in the literature concerned with personality, psychopathology and assessment. Empirical studies using bifactor analysis generally judge the estimated model using SEM model fit indices, which may lead to erroneous interpretations and conclusions. To address this problem, several researchers have proposed multiple criteria to assess bifactor models, such as a) conceptual grounds, b) overall model fit indices, and c) specific bifactor model indicators. In this article, we provide a brief summary of these criteria. An example using data gathered from a recently published research article is also provided to show how taking into account all criteria, rather than solely SEM model fit indices, may prevent researchers from drawing wrong conclusions. Facultad de Psicología. Laboratorio de Evaluación Psicológica y Educativa (LEPE) 2018-12-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/revaluar/article/view/22221 Revista Evaluar; Vol. 18 Núm. 3 (2018) 1667-4545 1515-1867 10.35670/1667-4545.v18.n3 spa https://revistas.unc.edu.ar/index.php/revaluar/article/view/22221/21819 Derechos de autor 2018 Pablo Ezequiel Flores-Kanter, Sergio Dominguez-Lara, Mario Alberto Trógolo, Leonardo Adrián Medrano http://creativecommons.org/licenses/by/4.0
institution	Universidad Nacional de Córdoba
institution_str	I-10
repository_str	R-10
container_title_str	Revistas de la UNC
language	Español
format	Artículo revista
topic	confirmatory factor analyses bifactor models PANAS complementary statistical fit indices confirmatory factor analyses bifactor models PANAS complementary statistical fit indices
spellingShingle	confirmatory factor analyses bifactor models PANAS complementary statistical fit indices confirmatory factor analyses bifactor models PANAS complementary statistical fit indices Flores-Kanter, Pablo Ezequiel Dominguez-Lara, Sergio Trógolo, Mario Alberto Medrano, Leonardo Adrián Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
topic_facet	confirmatory factor analyses bifactor models PANAS complementary statistical fit indices confirmatory factor analyses bifactor models PANAS complementary statistical fit indices
author	Flores-Kanter, Pablo Ezequiel Dominguez-Lara, Sergio Trógolo, Mario Alberto Medrano, Leonardo Adrián
author_facet	Flores-Kanter, Pablo Ezequiel Dominguez-Lara, Sergio Trógolo, Mario Alberto Medrano, Leonardo Adrián
author_sort	Flores-Kanter, Pablo Ezequiel
title	Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
title_short	Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
title_full	Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
title_fullStr	Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
title_full_unstemmed	Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators
title_sort	best practices in the use of bifactor models: conceptual grounds, fit indices and complementary indicators
description	Bifactor models have gained increasing popularity in the literature concerned with personality, psychopathology and assessment. Empirical studies using bifactor analysis generally judge the estimated model using SEM model fit indices, which may lead to erroneous interpretations and conclusions. To address this problem, several researchers have proposed multiple criteria to assess bifactor models, such as a) conceptual grounds, b) overall model fit indices, and c) specific bifactor model indicators. In this article, we provide a brief summary of these criteria. An example using data gathered from a recently published research article is also provided to show how taking into account all criteria, rather than solely SEM model fit indices, may prevent researchers from drawing wrong conclusions.
publisher	Facultad de Psicología. Laboratorio de Evaluación Psicológica y Educativa (LEPE)
publishDate	2018
url	https://revistas.unc.edu.ar/index.php/revaluar/article/view/22221
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first_indexed	2022-08-20T00:52:58Z
last_indexed	2022-08-20T00:52:58Z
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Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators

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