Journal of Communication | 2019
Easy Statistical Mediation Analysis With Distinguishable Dyadic Data
Abstract
The dyad is an important unit of human interaction found in many settings in life. Research on interpersonal relationships and outcomes that relies on measuring each member of a dyad on putative causes and effects can require complex analyses to illuminate how members of the dyad influence one another. Dyadic mediation analysis is a branch of mediation analysis that focuses on establishing the mechanism(s) by which mutual influence operate. Relying on the similarity between dyadic mediation analysis using structural equation modeling and mediation analysis using ordinary least squares regression, we developed MEDYAD, an easy-to-use computational tool for SPSS and SAS that conducts dyadic mediation analysis with distinguishable dyadic data. MEDYAD implements the Actor-Partner Interdependence Model extended to Mediation (APIMeM) as well as simpler and more complex dyadic mediation models defined by the number of mediators and whether variables in the model are mixed or between-dyad variables. Bootstrapping methods are implemented for inference about indirect effects. Additional features include methods for conducting all possible pairwise comparisons between indirect effects, heteroscedasticity-robust inference, and saving bootstrap estimates of mediation parameters for further analysis.