Network data involving three roles (e.g., sender, receiver, and target or perceiver) can be represented as a three-dimensional array. Such three-way networks arise naturally in social science research, but their analysis poses challenges. Although substantive questions often involve social mechanisms driving network change, no longitudinal methods for three-way networks currently exist. Moreover, data collection on three-way networks places a heavy burden on respondents, so sometimes only partial information is available. This talk presents two methodological contributions that start to address these limitations: a longitudinal model for fully observed three-way network data, and an inferential framework that uses two-way network data to learn about three-way relations. I will illustrate through applications what new empirical questions these methods enable us to address.
| Building: | West Hall |
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| Event Type: | Workshop / Seminar |
| Tags: | Aem Featured, seminar, statistics, symposium, Talk |
| Source: | Happening @ Michigan from Department of Statistics Seminar Series, Department of Statistics |
