Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 2 of 2
Full-Text Articles in Social and Behavioral Sciences
Global Network Inference From Ego Network Samples: Testing A Simulation Approach, Jeffrey A. Smith
Global Network Inference From Ego Network Samples: Testing A Simulation Approach, Jeffrey A. Smith
Department of Sociology: Faculty Publications
Network sampling poses a radical idea: that it is possible to measure global network structure without the full population coverage assumed in most network studies. Network sampling is only useful, however, if a researcher can produce accurate global network estimates. This article explores the practicality of making network inference, focusing on the approach introduced in Smith (2012). The method uses sampled ego network data and simulation techniques to make inference about the global features of the true, unknown network. The validity check here includes more difficult scenarios than previous tests, including those that go beyond the initial scope conditions of …
Macrostructure From Microstructure: Generating Whole Systems From Ego Networks, Jeffrey A. Smith
Macrostructure From Microstructure: Generating Whole Systems From Ego Networks, Jeffrey A. Smith
Department of Sociology: Faculty Publications
This paper presents a new simulation method to make global network inference from sampled data. The proposed simulation method takes sampled ego network data and uses Exponential Random Graph Models (ERGM) to reconstruct the features of the true, unknown network. After describing the method, the paper presents two validity checks of the approach: the first uses the 20 largest Add Health networks while the second uses the Sociology Coauthorship network in the 1990’s. For each test, I take random ego network samples from the known networks and use my method to make global network inference. I find that my method …