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

dc.creatorFlores-Kanter, Pablo Ezequiel
dc.creatorDominguez-Lara, Sergio
dc.creatorTrógolo, Mario Alberto
dc.creatorMedrano, Leonardo Adrián
dc.date2018-12-04
dc.date.accessioned2023-03-29T18:57:46Z
dc.date.available2023-03-29T18:57:46Z
dc.identifierhttps://revistas.unc.edu.ar/index.php/revaluar/article/view/22221
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6291053
dc.descriptionBifactor 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.en-US
dc.descriptionBifactor 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.es-ES
dc.formatapplication/pdf
dc.languagespa
dc.publisherFacultad de Psicología. Laboratorio de Evaluación Psicológica y Educativa (LEPE)es-ES
dc.relationhttps://revistas.unc.edu.ar/index.php/revaluar/article/view/22221/21819
dc.rightsDerechos de autor 2018 Pablo Ezequiel Flores-Kanter, Sergio Dominguez-Lara, Mario Alberto Trógolo, Leonardo Adrián Medranoes-ES
dc.rightshttp://creativecommons.org/licenses/by/4.0es-ES
dc.sourceRevista Evaluar; Vol. 18 Núm. 3 (2018)es-ES
dc.source1667-4545
dc.source1515-1867
dc.source10.35670/1667-4545.v18.n3
dc.subjectconfirmatory factor analysesen-US
dc.subjectbifactor modelsen-US
dc.subjectPANASen-US
dc.subjectcomplementary statistical fit indicesen-US
dc.subjectconfirmatory factor analyseses-ES
dc.subjectbifactor modelses-ES
dc.subjectPANASes-ES
dc.subjectcomplementary statistical fit indiceses-ES
dc.titleBest Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicatorsen-US
dc.titleBest Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicatorses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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