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 …

The development of stochastic models for the analysis of social networks is an important
growth area in contemporary statistics. The last few decades have witnessed the rapid …

Objectives The project aims to:(1) investigate structural and functional changes in an
Australian drug trafficking network across time to determine ways in which such networks …

Social networks are dynamic by nature. While network research has typically treated
relationships between social actors as static, there has been a surge in literature extending …

While several models for analysing longitudinal network data have been proposed, their
main differences, especially regarding the treatment of time, have not been discussed …

Statistical models for social networks, such as exponential random graphs (ERGMs), have
increasingly been used by organizational scholars to study the social interactions inside …

This paper compares several imputation methods for missing data in network analysis on a
diverse set of simulated networks under several missing data mechanisms. Previous work …

Missing data on network ties are a fundamental problem for network analysis. The biases
induced by missing edge data are widely acknowledged. In this paper, we present a new …

Organizations create networks with one another, and these networks may in turn shape the
organizations involved. Until recently, such complex dynamic processes could not be …

Given the growing number of available tools for modeling dynamic networks, the choice of a
suitable model becomes central. The goal of this survey is to provide an overview of tie …