Multilevel longitudinal analysis of social networks
将随机行为者导向模型扩展到多层网络面板数据，用贝叶斯方法估计随机系数，分析友谊网络与轻微违法行为的动态相互依赖，对研究网络动态和社会影响的学者有用。
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.