The effects of nonindependence are discussed for the analysis of data gathered in dyads and groups. For data in which each person is a member of one and only group, the Actor-partner Interdependence model is elaborated. For group data in which a person rates or interacts with every other member in the group, the Social Relations Model is emphasized. On the basis of theory and simulation, the authors provide practical advice concerning the optimal number of persons per research group, number of research groups, type of research design, and significance testing method.
Power depends more on group size than on number of groups.
Power is greater with the round-robin design than with the block design and greater with an asymptotic test of significance than with the usually used. The authors discuss the skew on theoretical power. In dyadic research, the responses of the two members of the dyad are likely to be nonindependent. Statistical estimation for three different processes that bring about non-independence are presented. In each, a variable X influences Y .