The social relations model (SRM) is typically used to identify sources of variance in interpersonal dispositions in families. Traditionally, it uses dyadic measurements that are obtained from a round-robin design, where each family member rates each other family member. Those dyadic measurements are mostly considered to be continuous, but we, however, wilt discuss how the SRM can be adapted to count dyadic measurements. Such SRM for count data can be formulated in the SEM-framework by viewing it as a confirmatory factor analysis (CFA), but it can also be defined in the multilevel framework. These two frameworks result in equivalent models of which the parameters can be estimated using maximum likelihood estimation or a Bayesian approach. We perform a simulation study to compare the performance of those two estimators. As an illustration, we consider intergenerational co-activity data from a block design and contrast family dynamics between non-divorced families and stepfamilies
