ABSTRACT
The analysis of dyadic data is not new (e.g., Fisher, 1925), but there has been a recent resurgence of interest in the field (Kenny, Kashy, & Cook, 2006). Dyadic data can be especially important in the developmental sciences because development is best considered within an appropriate context and much of this context involves individuals interacting with others. While dyadic data are central to many areas of study, a problem arises because these data often require special treatment due to the fact that they rarely conform to the traditional assumption of noninterdependent data. The purpose of this chapter is to provide a survey of the available methods for analyzing a particular type of dyadic data, that arising from interchangeable dyads. We provide a data example to show how such methods can be used to model data from a developmental perspective and what information can be gleaned from such analyses.
