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Incremental criterion prediction of personality facets over factors: obtaining unbiased estimates and confidence intervals
Many researchers have argued that higher order models of personality such as the Five Factor Model are insufficient, and that facet-level analysis is required to better understand criteria such as well-being, job performance, and personality disorders. However, common methods in the extant literature used to estimate the incremental prediction of facets over factors have several shortcomings. This paper delineates these shortcomings by evaluating alternative methods using statistical theory, simulation, and an empirical example. We recommend using differences between Olkin-Pratt adjusted r-squared for factor versus facet regression models to estimate the incremental prediction of facets and present a method for obtaining confidence intervals for such estimates using double adjusted-. r-squared bootstrapping. We also provide an R package that implements the proposed methods.
History
Journal
Journal of research in personalityVolume
53Pagination
148 - 157Publisher
Academic PressLocation
Maryland Heights, MOPublisher DOI
ISSN
0092-6566eISSN
1095-7251Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, ElsevierUsage metrics
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