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 (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. Public Significance Statement The present study illustrates the calibration procedure of an item pool to measure the Big Five personality traits according to the bifactor model. In addition, it is suggested that a multidimensional computerized adaptive test based on the bifactor model is more advantageous to assess the Big Five than other competing approaches (unidimensional computerized adaptive test, a multidimensional computerized adaptive test based on the correlated-factors model, and a short scale).