Modeling general and specific variance in multifaceted constructs: a comparison of the bifactor model to other approaches.

This article recommends an alternative method for testing multifaceted constructs. Researchers often have to choose between two problematic approaches for analyzing multifaceted constructs: the total score approach and the individual score approach. Both approaches can result in conceptual ambiguity. The proposed bifactor model assesses simultaneously the general construct shared by the facets and the specific facets, over and above the general construct. We illustrate the bifactor model by examining the construct of Extraversion as measured by the Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 1992), with two college samples (N = 383 and 378). The analysis reveals that the facets of the NEO-PI-R Extraversion correlate with criteria in opposite directions after partialling out the general construct. The direction of gender differences also varies by facets. Bifactor models combine the advantages but avoid the drawbacks of the 2 existing methods and can lead to greater conceptual clarity.