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We introduce a simple and extendable coevolution model for the analysis oflongitudinal network and nodal attribute data. The model features parametersthat describe three phenomena: homophily, contagion and autocorrelation of thenetwork and nodal attribute process. Homophily here describes how changes tothe network may be associated with between-node similarities in terms of theirnodal attributes. Contagion refers to how node-level attributes may changedepending on the network. The model we present is based upon a pair ofintertwined autoregressive processes. We obtain least-squares parameterestimates for continuous-valued fully-observed network and attribute data. Wealso provide methods for Bayesian inference in several other cases, includingordinal network and attribute data, and models involving latent nodalattributes. These model extensions are applied to an analysis of internationalrelations data and to data from a study of teen delinquency and friendshipnetworks.

Multiplicative Coevolution Regression Models for Longitudinal Networks and Nodal Attributes