The study of development across the lifespan has traditionally focused on the individual. However, dyadic designs within lifespan developmental methodology allow researchers to better understand individuals in a larger context that includes various familial relationships (husbands and wives, parents and children, and caregivers and patients). Dyadic designs involve data that are not independent, and thus outcome measures from dyad members need to be modeled as correlated. Typically, non-independent outcomes are appropriately modeled using multilevel or structural equation modeling approaches. Many dyadic researchers use the actor-partner interdependence model as a basic analysis framework, while new and exciting approaches are coming forth in the literature. Dyadic designs can be extended and applied in various ways, including with intensive longitudinal data (e.g., daily diaries), grid sequence analysis, repeated measures actor/partner interdependence models, and vector field diagrams. As researchers continue to use and expand upon dyadic designs, new methods for addressing dyadic research questions will be developed.