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
Descripción
Sumario: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)