Abstract
Sexual intercourse involves two people and many aspects of sexual health are influenced by, if not dependent on, interpersonal processes. Yet, the majority of sexual health research involves the study of individuals. The collection and analysis of dyadic data present additional complexities compared to the study of individuals. The aim of this article was to describe methods for the study of dyadic processes related to sexual health. One-sided designs, including the PLM, involve a single individual reporting on the characteristics of multiple romantic or sexual relationships and the associations of these factors with sexual health outcomes are then estimated. This approach has been used to study how relationship factors, such as if the relationship is serious or casual, are associated with engagement in HIV risk behaviors. Such data can be collected cross-sectionally, longitudinally or through the use of diaries. Two-sided designs, including the actor-partner interdependence model, are used when data are obtained from both members of the dyad. The goal of such approaches is to disentangle intra- and inter-personal effects on outcomes (e.g., the ages of an individual and his partner may influence sexual frequency). In distinguishable datasets, there is some variable that allows the analyst to differentiate between partners within dyads, such as HIV status in a serodiscordant couple. When analyzing data from these dyads, effects can be assigned to specific types of partners. In exchangeable dyadic datasets, no variable is present that distinguishes between couple members across all dyads. Extensions of these approaches are described.