A Mega-Analysis of Personality Prediction: Robustness and Boundary Conditions
January 27, 2021 12:30 - 13:30
Emorie Beck, Northwestern University Feinberg School of Medicine
Decades of studies identify personality traits as an important predictor of life outcomes. However, previous investigations of personality-outcome associations have not taken a principled approach to covariate use or other sampling strategies to ensure the robustness of personality-outcome associations. The result is that it is unclear (1) whether personality predicts important outcomes after accounting for a range of background variables, (2) for whom and when personality predictions hold, and 3) which background variables are most important to account for. The present study examines the robustness and boundary conditions of personality prediction using the 14 personality characteristics to predict 14 health, social, education/work, and societal outcomes across eight different person- and study-level moderators using individual participant data from 171,395 individuals across 10 longitudinal panel studies in a mega-analytic framework. Robustness and boundary conditions were systematically tested using propensity score matching. Personality traits were robust predictors of life outcomes, and those effects generalize, as there were few moderators of personality-outcome associations. In sum, personality is a powerful predictor of life outcomes with few moderated associations.
You can find the preprint and supplemental materials here: https://psyarxiv.com/7pg9b/