Easy Statistical Mediation Analysis With Distinguishable Dyadic Data

Abstract Research in communication and other social science disciplines 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 operates. Relying on the similarity between dyadic mediation analysis using structural equation modeling and mediation analysis with ordinary least squares regression, we developed MEDYAD, an easy-to-use computational tool for SPSS, SAS, and R 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. Bootstrapping methods are implemented for inferences about indirect effects. Additional features include methods for conducting all possible pairwise comparisons between indirect effects, heteroskedasticity-robust inference, and saving bootstrap estimates of parameters for further analysis.