Tracing the Interpersonal Web of Psychopathology: Dyadic Data Analysis Methods for Clinical Researchers

Abstract

Recent advances in dyadic data analysis techniques, which treat the dyad, rather than the individual, as the unit of analysis, offer great potential for clinical researchers studying psychopathology. Accordingly, the present article provides readers with a foundation for understanding how the web of interpersonal processes surrounding psychopathology can be modeled and analyzed. The authors start by describing why the analysis of dyadic behaviour may be particularly important for clinical researchers and how issues of dependence that lie at the heart of dyadic data may be productively studied. Next, they describe design issues to consider when studying the interactions of dyads, as well as different kinds of outcome and predictor variables and their data-analytic implications. They introduce the actor-partner interdependence model (APIM), and explain in detail how to estimate it using structural equation modeling (SEM) for both distinguishable and indistinguishable dyads. Extensions of the basic APIM to allow for moderation and mediation, as well as alternative dyadic models involving dyadic latent variables are also covered. Toward the end of the article, the authors describe various approaches for incorporating psychopathology into dyadic SEMs and provide a list of basic questions for clinical researchers to consider when setting up a dyadic model for data analysis.