Date of Award
Doctor of Philosophy (PhD)
Decades of research suggest that personality is an important and robust predictor of life outcomes. However, previous investigations of personality-outcome associations have not adequately accounted for reverse causality and selection bias nor have they examined the boundary conditions of the effects, which has left the robustness conditions of personality-outcome associations unknown. The present study examines the robustness and boundary conditions of personality prediction using 14 personality characteristics to predict 14 health, social, education/work, and societal life outcomes across eight different person- and study-level moderators in 10 longitudinal panel studies in a mega-analytic framework coupled with propensity score matching to control for selection bias and specification curve analysis to test boundary conditions. In doing so, it is perhaps the most comprehensive test of personality prediction to date, both in scope and through the measures to taken to ensure that the estimates of personality-outcome associations were robust. Despite these measures, personality was a robust predictor of outcomes in both the propensity score matching and specification curve analysis studies. Moreover, relative to main effects of personality predicting outcomes, there were fewer moderators of personality-outcome associations. In sum, personality prediction, even over decades, was quite robust – across studies, personality characteristics, outcomes, moderators, and covariates. Personality is a powerful predictor of life outcomes.
Chair and Committee
Joshua J. Jackson
Patrick L. Hill, Randy Larsen, David Condon, Thomas Oltmanns,
Beck, Emorie Danielle, "A Mega-Analysis of Personality Prediction: Robustness and Boundary Conditions" (2020). Arts & Sciences Electronic Theses and Dissertations. 2303.