A default Bayesian hypothesis test for mediation

M.B. Nuijten, R. Wetzels, D. Matzke, E.J. Wagenmakers, C.V. Dolan

Research output: Contribution to journalArticleScientificpeer-review

35 Citations (Scopus)
134 Downloads (Pure)

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).
Original languageEnglish
Pages (from-to)85-97
JournalBehavior Research Methods
Volume47
Issue number1
DOIs
Publication statusPublished - 2015

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