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...
| Autores: | , , , |
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| 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 |
| 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) |
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