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A mixed effects model for longitudinal relational and network data, with applications to international trade and conflict. (English) Zbl 1454.62509

Summary: The focus of this paper is an approach to the modeling of longitudinal social network or relational data. Such data arise from measurements on pairs of objects or actors made at regular temporal intervals, resulting in a social network for each point in time. In this article we represent the network and temporal dependencies with a random effects model, resulting in a stochastic process defined by a set of stationary covariance matrices. Our approach builds upon the social relations models of R. M. Warner et al. [“A new round robin analysis of variance for social interaction data”, J. Personal. Soc. Psychol. 37, No. 10, 1742–1757 (1979; doi:10.1037/0022-3514.37.10.1742)] and P. S. Gill and T. B. Swartz [Can. J. Stat. 29, No. 2, 321–331 (2001; Zbl 0974.62112)] and allows for an intra- and inter-temporal representation of network structures. We apply the methodology to two longitudinal data sets: international trade (continuous response) and militarized interstate disputes (binary response).

MSC:

62P25 Applications of statistics to social sciences
62F15 Bayesian inference
91D30 Social networks; opinion dynamics

Citations:

Zbl 0974.62112
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References:

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