Models of interdependent individuals versus dyadic processes in relationship research

Abstract

In this article, we consider the statistical models that are appropriate to understand relationship processes between two people who are in a committed relationship. Some of these processes capture inherently individual processes where individuals happen to be interrelated and others capture inherently dyadic processes. We compare several different statistical approaches to model these phenomena, including the actor–partner interdependence model, common fate model, and a dyadic score model. We compare and contrast these models using a data set on closeness and time spent together from 201 couples where one partner is distinguished by stress associated with an upcoming professional exam. The models yield results that appear to give different interpretations of the data. We discuss situations in which each model may be preferred and invite relationship researchers to model relationship data using the statistical model that matches their conceptual framework, rather than using a rigid statistical methodology.

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