A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power

Quentin F. Gronau*, Sara van Erp, Daniel W. Heck, Joseph Cesario, Kai J. Jonas, Eric-Jan Wagenmakers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Earlier work found that – compared to participants who adopted constrictive body postures – participants who adopted expansive body postures reported feeling more powerful, showed an increase in testosterone and a decrease in cortisol, and displayed an increased tolerance for risk. However, these power pose effects have recently come under considerable scrutiny. Here, we present a bayesian meta-analysis of six preregistered studies from this special issue, focusing on the effect of power posing on felt power. Our analysis improves on standard classical meta-analyses in several ways. First and foremost, we considered only preregistered studies, eliminating concerns about publication bias. Second, the bayesian approach enables us to quantify evidence for both the alternative and the null hypothesis. Third, we use bayesian model-averaging to account for the uncertainty with respect to the choice for a fixed-effect model or a random-effect model. Fourth, based on a literature review, we obtained an empirically informed prior distribution for the between-study heterogeneity of effect sizes. This empirically informed prior can serve as a default choice not only for the investigation of the power pose effect but for effects in the field of psychology more generally. For effect size, we considered a default and an informed prior. Our meta-analysis yields very strong evidence for an effect of power posing on felt power. However, when the analysis is restricted to participants unfamiliar with the effect, the meta-analysis yields evidence that is only moderate.
Original languageEnglish
Pages (from-to)123-138
JournalComprehensive Results in Social Psychology
Issue number1
Publication statusPublished - 2017

Cite this