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WS-M08: Introduction to inference with networks in R
Time:
Monday, 23/June/2025:
9:00am - 12:00pm
Session Chair: Tomas Diviak Session Chair: Robert W Krause Session Chair: Filip Agneessens Session Chair: James Hollway
Session Abstract
This 3-hour workshop provides an introduction to statistical methods for analyzing social networks. The focus is on nodal and dyadic level analysis. We will be using R packages migraph, sna, and xUCINET to perform these analyses.
The course outline is as follows:
1) testing a network’s basic properties using conditional uniform graph (CUG) test (e.g., reciprocity, homophily)
2) nodal level statistical tests
3) permutation-based comparisons between groups of nodes
4) QAP correlation and linear regression – the underlying logic of QAP, data format etc.
5) QAP GLM – logistic, poisson, cognitive-social-structures, and other types and extensions
Presentations
Introduction to inference with networks in R
Robert W Krause, Tomas Diviak, Filip Agneessens, James Hollway
This 3-hour workshop provides an introduction to statistical methods for analyzing social networks. The focus is on nodal and dyadic level analysis. We will be using R packages migraph, sna, and xUCINET to perform these analyses.
The course outline is as follows:
1) testing a network’s basic properties using conditional uniform graph (CUG) test (e.g., reciprocity, homophily)
2) nodal level statistical tests
3) permutation-based comparisons between groups of nodes
4) QAP correlation and linear regression – the underlying logic of QAP, data format etc.
5) QAP GLM – logistic, poisson, cognitive-social-structures, and other types and extensions
