Although longitudinal social network data are increasingly collected, there are few guides on how to navigate the range of available tools for longitudinal network analysis. The applied social scientist is left to wonder: Which model is most appropriate for my data? How should I get started with this modeling strategy? And how do I know if my model is any good? This book answers these questions. Author Scott Duxbury assumes that the reader is familiar with network measurement, d...
Tabela de Conteúdo
Chapter 1. Introduction
Chapter 2: Temporal Exponential Random Graph Models
Chapter 3: Stochastic Actor-oriented Models
Chapter 4: Modeling Relational Event Data
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Sobre o autor
Scott Duxbury is an Assistant Professor of Sociology at the University of North Carolina at Chapel Hill. His research examines drug markets, criminal networks, qu...
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