Journal
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 4
Volume 4, Issue -, Pages 343-363Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-statistics-060116-054035
Keywords
social networks; statistical modeling; inference
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This article discusses the stochastic actor-oriented model for analyzing panel data of networks. The model is defined as a continuous-time Markov chain, observed at two or more discrete time moments. It can be regarded as a generalized linear model with a large amount of missing data. Several estimation methods are discussed. After presenting the model for evolution of networks, attention is given to coevolution models. These use the same approach of a continuous-time Markov chain observed at a small number of time points, but now with an extended state space. The state space can be, for example, the combination of a network and nodal variables, or a combination of several networks. This leads to models for the dynamics of multivariate networks. The article emphasizes the approach to modeling and algorithmic issues for estimation; some attention is given to comparison with other models.
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