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<p>On this page you can find additional information for the paper "A default Bayesian hypothesis test for mediation" (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2015).</p> <p>All simulation codes are available. The R package BayesMed is available from CRAN: <a href="http://cran.r-project.org/web/packages/BayesMed/index.html" rel="nofollow">http://cran.r-project.org/web/packages/BayesMed/index.html</a>.</p> <p><strong>Abstract</strong></p> <p>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 eff?ect 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 (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 Je?ffreys-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.</p> <p><strong>References</strong></p> <p>Nuijten, M. B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E.-J. (2015). A default Bayesian hypothesis test for mediation. Behavior Research Methods, 47, 85-97. </p> <p>Yuan, Y., & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods, 14 , 301-322.</p>
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