facial_feedback: Data Set: Facial Feedback

In metaBMA: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Data Set: Facial Feedback

Description

Preregistered replication (Wagenmakers et al., 2016) that investigated the facial feedback hypothesis (Strack, Martin, & Stepper, 1988).

Usage

facial_feedback

Format

A data frame with three variables:

study

Authors of original study (see Wagenmakers et. al, 2016)

d

Measure of effect size: Cohen's d (difference between smile vs. pout condition)

SE

Measure of precision: standard error of Cohen's d

Details

The facial-feedback hypothesis states that people's affective responses can be influenced by their own facial expression (e.g., smiling, pouting), even when their expression did not result from their emotional experiences (Strack, Martin, & Stepper, 1988).

References

Strack, F., Martin, L. L., & Stepper, S. (1988). Inhibiting and facilitating conditions of the human smile: A nonobtrusive test of the facial feedback hypothesis. Journal of Personality and Social Psychology, 54, 768–777. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/0022-3514.54.5.768")}

Wagenmakers, E.-J., Beek, T., Dijkhoff, L., Gronau, Q. F., Acosta, A., Adams, R. B., ... Zwaan, R. A. (2016). Registered replication report: Strack, Martin, & Stepper (1988). Perspectives on Psychological Science, 11, 917-928. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/1745691616674458")}

Examples

data(facial_feedback)
head(facial_feedback)
mf <- meta_fixed(d, SE, study, facial_feedback)
mf
plot_posterior(mf)

metaBMA documentation built on Sept. 13, 2023, 9:06 a.m.