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.
สารบัญ
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
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Jenine K. Harris earned her doctorate in public health studies and biostatistics from Saint Louis University School of Public Health in 2008. Currently, she teaches biostatistics courses as an Associate Professor in the Brown School public health program at Washington University in St. Louis. In 2013, she authored An Introduction to Exponential Random Graph Modeling, which was published in the Sage Quantitative Applications in the Social Sciences series and is accompanied by the ergmharris R package available on the Comprehensive R Archive Network (CRAN). She is an author on more than 80 peer-reviewed publications, and developed and published the odds.n.ends R package available on the CRAN. She is the leader of R-Ladies St. Louis, which she co-founded with Chelsea West in 2017 (@rladiesstl). R-Ladies St. Louis is a local chapter of R-Ladies Global (@rladiesglobal), an organization devoted promoting gender diversity in the R community. Her recent research interests focus on improving the quality of research in public health by using reproducible research practices throughout the research process.
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