Assessing the Big Five with bifactor computerized adaptive testing

Multidimensional computerized adaptive testing based on the bifactor model (MCAT-B) can provide efficient assessments of multifaceted constructs. In this study, MCAT-B was compared with a short fixed-length scale and computerized adaptive testing based on unidimensional (UCAT) and multidimensional (...

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Detalles Bibliográficos
Autores: Nieto, María Dolores, Abad García, Francisco José, Olea Díaz, Julio
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/718286
Acceso en línea:http://hdl.handle.net/10486/718286
https://dx.doi.org/10.1037/pas0000631
Access Level:acceso abierto
Palabra clave:personality assessment
Big Five
item response theory
multidimensional computerized adaptive testing (MCAT)
bifactor model
Psicología
Descripción
Sumario:Multidimensional computerized adaptive testing based on the bifactor model (MCAT-B) can provide efficient assessments of multifaceted constructs. In this study, MCAT-B was compared with a short fixed-length scale and computerized adaptive testing based on unidimensional (UCAT) and multidimensional (correlated-factors) models (MCAT) to measure the Big Five model of personality. The sample comprised 826 respondents who completed a pool with 360 personality items measuring the Big Five domains and facets. The dimensionality of the Big Five domains was also tested. With only 12 items per domain, the MCAT and MCAT-B procedures were more efficient to assess highly multidimensional constructs (e.g., Agreeableness), whereas no differences were found with UCAT and the short scale with traits that were essentially unidimensional (e.g., Extraversion). Furthermore, the study showed that MCAT and MCAT-B provide better content-balance of the pool because, for each Big Five domain, items from all the facets are selected in similar proportions