Comparing Two Models of Dyadic Change: Correlated Growth Versus Common Fate

Abstract

The analysis of longitudinal dyadic data often requires complex structural models. Two models of dyadic change, the correlated growth model and the common fate growth model, differ in their description of change. The correlated growth model estimates separate but correlated growth trajectories for each member of a dyad. The common fate growth model treats the dyad as the unit of analysis and estimates growth parameters for the dyad. Relationship and life satisfaction are important outcomes that feature prominently in the relationship literature and must be modeled adequately to be understood. In a sample of 325 romantic couples, the relative efficacy of these two models for describing change in relationship and life satisfaction is compared. The common fate growth model better described relationship satisfaction, while the correlated growth model provided superior fit to life satisfaction. Implications for the modeling of dyadic data are discussed.