An Introduction to Exponential Random Graph Modeling
eBook - ePub

An Introduction to Exponential Random Graph Modeling

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

An Introduction to Exponential Random Graph Modeling

About this book

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. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. This book fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.

An Introduction to Exponential Random Graph Modeling is a part of SAGE's Quantitative Applications in the Social Sciences (QASS) series, which has helped countless students, instructors, and researchers learn cutting-edge quantitative techniques.

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Yes, you can access An Introduction to Exponential Random Graph Modeling by Jenine K. Harris in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Halftitle
  3. Quantitative Applications in the Social Sciences
  4. Title
  5. Copyright
  6. Contents
  7. Acknowledgments
  8. About the Author
  9. Series Editor’S Introduction
  10. 1 The Promise and Challenge of Network Approaches
  11. 2 Statistical Network Models
  12. 3 Building a Useful Exponential Random Graph Model
  13. 4 Extensions of the Basic Model for Directed Networks and Using Dyadic Attributes as Predictors
  14. 5 Conclusion and Recommendations
  15. Appendix: Triad Types in Directed Networks
  16. References
  17. Index
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