Published online by Cambridge University Press: 08 June 2017
We investigate the effect of personality on prosocial behavior in a Bayesian multilevel meta-analysis (MLMA) of 15 published, interdisciplinary experimental studies. With data from the 15 studies constituting nearly 2500 individual observations, we find that the Big Five traits of Agreeableness and Openness are significantly and positively associated with prosocial behavior, while none of the other three traits are. These results are robust to a number of different model specifications and operationalizations of prosociality, and they greatly clarify the contradictory findings in the literature on the relationship between personality and prosocial behavior. Though previous research has indicated that incentivized experiments result in reduced prosocial behavior, we find no evidence that monetary incentivization of participants affects prosocial tendencies. By leveraging individual observations from multiple studies and explicitly modeling the multilevel structure of the data, MLMA permits the simultaneous estimation of study- and individual-level effects. The Bayesian approach allows us to estimate study-level effects in an unbiased and efficient manner, even with a relatively small number of studies. We conclude by discussing the limitations of our study and the advantages and disadvantages of the MLMA method.
Reuben Kline, Department of Political Science, Center for Behavioral Political Economy, Stony Brook University, SUNY 4392, Stony Brook, NY 11794 (firstname.lastname@example.org). Alexa Bankert, Assistant Professor, Department of Political Science, School of Public and International Affairs, University of Georgia, 104 Baldwin St, Athens, GA 30602, (email@example.com). Lindsey Levitan, Associate Professor, Department of Psychology, Shepherd University, 301 N King Street, Shepherdstown, WV 25443, (firstname.lastname@example.org). Patrick Kraft, Ph.D. Candidate, Department of Political Science, Stony Brook University, Stony Brook, NY 11794-4392, (email@example.com). The authors would like to thank those who generously shared their data with the authors. The authors also thank two anonymous reviewers and the editors for their helpful suggestions which greatly improved the paper. To view supplementary material for this article, please visit http://dx.doi.org/10.1017/psrm.2017.14
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