An Introduction to Exponential Random Graph Modeling (Quantitative Applications in the Social Sciences 173)

An Introduction to Exponential Random Graph Modeling (Quantitative Applications in the Social Sciences 173)

By: Jenine K. Harris (author)Paperback

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This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. By using examples from public health, this book walks the reader through the process of ERGM model-building using R statistical software and the statnet package.

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About Author

Jenine K. Harris, PhD is an assistant professor in the Brown School at Washington University in St. Louis where she teaches biostatistics courses in the public health and social work graduate programs. She worked closely with network scientist Douglas A. Luke on the use of social network approaches to understanding public health systems. Her current research employs complex statistical network models to better understand communication networks connecting local health departments nationwide, especially social media connections. Dr. Harris has published over 40 articles in respected outlets such as the American Journal of Public Health and the American Journal of Preventive Medicine. Her 2012 article "Methods in public health services and systems research: a systematic review" was selected as one of the most notable public health systems research (PHSR) articles published in 2012 by the PHSR Interest Group at AcademyHealth.


1. The Promise and Challenge of Network Approaches 2. Statistical Network Models 3. Building a Useful Exponential Random Graph Model 4. Extensions of the Basic Model for Directed Networks and Using Dyadic Attributes as Predictors 5. Conclusion and Recommendations

Product Details

  • publication date: 18/02/2014
  • ISBN13: 9781452220802
  • Format: Paperback
  • Number Of Pages: 136
  • ID: 9781452220802
  • weight: 159
  • ISBN10: 1452220808

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