Multilevel longitudinal analysis of social networks

Johan Koskinen; Tom A B Snijders

doi:10.1093/jrsssa/qnac009

Multilevel longitudinal analysis of social networks

J R Stat Soc Ser A Stat Soc. 2023 Jan 23;186(3):376-400. doi: 10.1093/jrsssa/qnac009. eCollection 2023 Jul.

Authors

Johan Koskinen^{1

2}, Tom A B Snijders^{3

4}

Affiliations

¹ University of Stockholm, Stockholm, Sweden.
² University of Melbourne, Melbourne, Australia.
³ University of Oxford, Oxford, UK.
⁴ University of Groningen, Groningen, The Netherlands.

Abstract

Stochastic actor-oriented models (SAOMs) are a modelling framework for analysing network dynamics using network panel data. This paper extends the SAOM to the analysis of multilevel network panels through a random coefficient model, estimated with a Bayesian approach. The proposed model allows testing theories about network dynamics, social influence, and interdependence of multiple networks. It is illustrated by a study of the dynamic interdependence of friendship networks and minor delinquency. Data were available for 126 classrooms in the first year of secondary school, of which 82 were used, containing relatively few missing data points and having not too much network turnover.

Keywords: MCMC; delinquency; random coefficient model; social influence; stochastic actor-oriented model; two-mode network.