Milica Miocevic (McGill University)

Title: Bayesian Mediation Analysis

Abstract: Mediation analysis is used to study intermediate variables (M) that transmit the effect of an independent variable (X) on a dependent variable (Y). For example, an intervention designed to reduce unhealthy habits (X) might affect fruit and vegetable consumption (M), which in turn might affect general health (Y). In this hypothetical study, the quantity of interest is the indirect effect of the intervention on general health through fruit and vegetable consumption. Mediation analysis can be performed using both classical (frequentist) and Bayesian approaches. In recent years social science researchers have turned to Bayesian methods when they encounter convergence issues (Chen, Choi, Weiss, & Stapleton, 2014), issues due to small samples (Lee & Song, 2004), and when they wish to report the probability that a parameter lies within a certain interval (Rindskopf, 2012). The distribution of the mediated effect is often asymmetric (Craig, 1936; Lomnicki, 1967; Springer & Thompson, 1966), and the best classical methods for evaluating the significance of the mediated effect either take the asymmetric distribution of the product into account or make no distributional assumptions at all (Cheung 2007, 2009; MacKinnon, Fritz, Williams, & Lockwood 2007; MacKinnon, Lockwood, & Williams, 2004; MacKinnon, Lockwood, Hoffmann, West, & Sheets, 2002; MacKinnon, et al., 1995; Shrout & Bolger, 2002; Tofighi & MacKinnon, 2011; Valente, Gonzalez, Miočević, & MacKinnon, 2016; Yuan & MacKinnon, 2009). Bayesian methods can easily accommodate the asymmetric distributions of the mediated effect and other functions of the mediated effect, e.g. effect size measures and causal estimates of indirect and direct effects. Furthermore, Bayesian methods provide an intuitive framework for the inclusion of relevant prior information into the statistical analysis. In this talk I will discuss the advantages of Bayesian mediation analysis, summarize recommendations that can be made for applied researchers based on the methodological literature on Bayesian mediation analysis thus far, and conclude with future directions for this line of research.