Examining cross-level effects in dyadic analysis: A structural equation modeling perspective

Abstract

The actor–partner interdependence (APIM) and common-fate (CFM) models for dyadic data are well understood and widely applied. The actor and partner coefficients estimated in the APIM reflect the associations between individual-level variance components, whereas the CFM coefficient describes the association between dyad-level variance components. Additionally, both models assume that the theoretically relevant and/or empirically dominant component of variability resides at the same level (individual or dyad) across the predictor and outcome variables. The present work recasts the APIM and CFM in terms of dyadic nonindependence, or the extent to which a given variable reflects dyad- versus individual-level processes, and describes a pair of hybrid actor–partner and common-fate models that connect variance components residing at different levels. A series of didactic examples illustrate how the traditional APIM and CFM can be combined with the hybrid models to describe mediational processes that span the individual and dyad levels.