Growth modeling is a useful tool for studying change over time, and it is becoming increasingly popular with developmental researchers. There is a considerable methodological literature surrounding growth modeling for individuals; however, far less attention has been focused on growth models for pairs of related individuals (i.e., dyads). In this article, the authors consider dyadic growth models for those cases where there are no relevant variables that can empirically distinguish between dyad members (e.g., same-sex twins or best friends). The authors describe how researchers can estimate growth models for indistinguishable dyads using both multilevel modeling and structural equation modeling. Although both approaches can be used to estimate the same underlying models, the authors focus on practical similarities and differences between the two approaches. They illustrate modeling issues using an overtime study of adolescent twins' conflict with their mothers, a substantively important topic given the enduring interest in parent-child relationships during adolescence.