title: A default Bayesian hypothesis test for mediation.
abstract: In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).
authors.affiliation: Tilburg University, Tilburg, The Netherlands.
authors.forename: Michèle B
authors.initials: MB
authors.lastname: Nuijten
authors.forename: Ruud
authors.initials: R
authors.lastname: Wetzels
authors.forename: Dora
authors.initials: D
authors.lastname: Matzke
authors.forename: Conor V
authors.initials: CV
authors.lastname: Dolan
authors.forename: Eric-Jan
authors.initials: EJ
authors.lastname: Wagenmakers
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D008390:Markov Chains; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D017008:Negotiating; D012107:Research Design