• Open Access

Hierarchical longitudinal models of relationships in social networks


Address for correspondence: A. James O'Malley, Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115-5899, USA. E-mail: omalley@hcp.med.harvard.edu


Motivated by the need to understand the dynamics of relationship formation and dissolution over time in real world social networks we develop a new longitudinal model for transitions in the relationship status of pairs of individuals (‘dyads’). We first specify a model for the relationship status of a single dyad and then extend it to account for important interdyad dependences (e.g. transitivity—‘a friend of a friend is a friend’) and heterogeneity. Model parameters are estimated by using Bayesian analysis implemented via Markov chain Monte Carlo sampling. We use the model to perform novel analyses of two diverse longitudinal friendship networks: an excerpt of the Teenage Friends and Lifestyle Study (a moderately sized network) and the Framingham Heart Study (a large network).