R/data_facial_feedback.R

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

#' Data Set: Facial Feedback
#'
#' Preregistered replication (Wagenmakers et al., 2016) that investigated the
#' facial feedback hypothesis (Strack, Martin, & Stepper, 1988).
#' @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).
#'
#' @format A data frame with three variables:
#' \describe{
#'   \item{\code{study}}{Authors of original study (see Wagenmakers et. al, 2016)}
#'   \item{\code{d}}{Measure of effect size: Cohen's d (difference between smile vs. pout condition)}
#'   \item{\code{SE}}{Measure of precision: standard error of Cohen's d}
#' }
#' @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.
#' \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. \doi{10.1177/1745691616674458}
#' @examples
#' data(facial_feedback)
#' head(facial_feedback)
#' mf <- meta_fixed(d, SE, study, facial_feedback)
#' mf
#' plot_posterior(mf)
"facial_feedback"