Events & Calendars Statistics and Data Science Colloquium: Regression Methods for Network Indexed Data: Modeling Occurrences of Burglary and Identifying Correlates of Injection Drug Use Cessation

We begin by defining and providing examples of network-indexed data. We then turn to two applications: modeling occurrences of residential burglary in Boston and identifying network predictors of injection drug use cessation among a group of drug users in rural Kentucky. We discuss the graph Laplacian, a hierarchical regression model and generalized estimating equations along the way.

Bio: Elizabeth Upton completed her Ph.D. in statistics at Boston University. Her research focuses on network science, particularly adapting regression methodologies to network-indexed data. Before attending BU, Elizabeth taught high school math for three years and worked in finance as a quantitative analyst. She currently is an assistant professor at Williams College. Outside of her research and work interests, Elizabeth enjoys spending time with her family, skiing and cheering on the New England Patriots.

*The link will be sent to the Math & Stats listserv on the day of the event. If you are not part of that group and would like to attend, please email kglista@amherst.edu, and the link will be sent the day of the event.