Egocentric Network Data Analysis with ERGMs
Michal Bojanowski, Pavel Krivitsky
This workshop provides an introduction to analyzing egocentrically sampled data with exponential-family random graph models (ERGMs) for statistical network analysis. It is a hands-on workshop demonstrating how to fit, diagnose and simulate both static and dynamic ERG models from such data, using the ergm.ego package, part of the integrated Statnet software collection in R. Topics covered in this session include:
- a review of approaches to analyzing egocentrically sampled data
- an overview of the statistical theory that supports the use of ERGMs for egocentrically sampled networks
- defining and fitting ERGMs to egocentric data
- interpreting model coefficients
- checking goodness-of-fit and model adequacy
- simulating complete networks from the specified ERG models.
This workshop assumes basic familiarity with R, experience with network concepts, terminology and data, and familiarity with the basic principles of statistical modeling and inference. Previous experience with ERGMs is not required, but is strongly recommended (the introductory ERGM workshop is a good place to start).