Assessing Mediation in Dyadic Data Using the Actor-Partner Interdependence Model

TLDR

Mediation assessment in dyadic data is crucial for testing process models, yet becomes complex with the actor–partner interdependence model, particularly when dyad members are distinguishable such as in heterosexual couples. The study demonstrates how assuming specific dyadic patterns can reduce model complexity and illustrates mediation assessment strategies using data from heterosexual couples. The authors employ structural equation modeling with phantom models to test specific mediating effects and contrasts, enabling point estimates and bootstrap intervals, and illustrate these methods using data from heterosexual couples. Keywords: mediation, dyadic data, APIM, phantom models, bootstrapping.

Abstract

Abstract The assessment of mediation in dyadic data is an important issue if researchers are to test process models. Using an extended version of the actor–partner interdependence model the estimation and testing of mediation is complex, especially when dyad members are distinguishable (e.g., heterosexual couples). We show how the complexity of the model can be reduced by assuming specific dyadic patterns. Using structural equation modeling, we demonstrate how specific mediating effects and contrasts among effects can be tested by phantom models that permit point and bootstrap interval estimates. We illustrate the assessment of mediation and the strategies to simplify the model using data from heterosexual couples. Keywords: mediationdyadic dataAPIMphantom modelsbootstrapping