![]() Facets explained more than twice the variance of domains. Facets of gregariousness and excitement seeking had stronger negative correlations, and openness to aesthetics, feelings, and values had stronger positive correlations with crystallized than fluid intelligence. At the facet-level, traits related to intellectual engagement and unconventionality were more strongly related to intelligence than other openness facets, and sociability and orderliness were negatively correlated with intelligence. 20) and neuroticism (ρ = -.09) were the strongest Big Five correlates of intelligence and that openness correlated more with crystallized than fluid intelligence. The study was complemented by four of our own unpublished datasets (N = 26,813) which were used to assess the ability of item-level models to provide generalizable prediction. Age and sex differences in personality and intelligence, and study-level moderators, are also examined. It provides the first meta-analysis of personality and intelligence to comprehensively examine (a) facet-level correlations for these hierarchical frameworks of personality, (b) item-level correlations, (c) domain- and facet-level predictive models. It presents a meta-analysis (N = 162,636, k = 272) of domain, facet, and item-level correlations between personality and intelligence (general, fluid, and crystallized) for the major Big Five and HEXACO hierarchical frameworks of personality: NEO PI-R, Big Five Aspect Scales (BFAS), BFI-2, and HEXACO PI R. This study provides a comprehensive assessment of the associations of personality and intelligence. (PsycINFO Database Record (c) 2014 APA, all rights reserved). ![]() We conclude that nonlinear models can provide incremental detail regarding personality and intelligence associations. We discuss how suited current theories of the personality-intelligence interface are to explain these associations, and how research on intellectually gifted samples may provide a unique way of understanding them. Quadratic associations explained substantive variance above and beyond linear effects (mean R² between 1.8% and 3.6%) for Sociability, Maturity, Vigor, and Leadership in males and Sociability, Maturity, and Tidiness in females linear associations were predominant for other traits. Of these, 53% were supported in all 4 male grades and 58% in all 4 female grades. On the basis of the literature, we made 17 directional hypotheses for the linear and quadratic associations. We departed from previous studies, including one with PT (Reeve, Meyer, & Bonaccio, 2006), by modeling latent quadratic effects directly, controlling the influence of the common factor in the personality scales, and assuming a direction of effect from g to personality. Using 2 techniques, quadratic and generalized additive models, we tested for linear and nonlinear associations of general intelligence (g) with 10 personality scales from Project TALENT (PT), a nationally representative sample of approximately 400,000 American high school students from 1960, divided into 4 grade samples (Flanagan et al., 1962). Yet, there are no a priori reasons why linear relations should be expected over nonlinear ones, which represent a much larger set of all possible associations. ![]() Research on the relations of personality traits to intelligence has primarily been concerned with linear associations. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |