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BEGIN:VEVENT
UID:20211201T144913EST-26279f42fa@www.amherst.edu/node/781261
DTSTAMP:20211201T194913Z
CATEGORIES:Amherst Event
DESCRIPTION:We begin by defining and providing examples of network-indexed
data. We then turn to two applications: modeling occurrences of residentia
l burglary in Boston and identifying network predictors of injection drug
use cessation among a group of drug users in rural Kentucky. We discuss th
e graph Laplacian\, a hierarchical regression model and generalized estima
ting equations along the way.\n\nBio: Elizabeth Upton completed her Ph.D.
in statistics at Boston University. Her research focuses on network scien
ce\, particularly adapting regression methodologies to network-indexed dat
a. Before attending BU\, Elizabeth taught high school math for three years
and worked in finance as a quantitative analyst. She currently is an assi
stant professor at Williams College. Outside of her research and work inte
rests\, Elizabeth enjoys spending time with her family\, skiing and cheeri
ng on the New England Patriots. \n\n*The link will be sent to the Math &a
mp\; Stats listserv on the day of the event. If you are not part of that g
roup and would like to attend\, please email kglista@amherst.edu\, and the
link will be sent the day of the event.
DTSTART:20201015T213000Z
DTEND:20201015T223000Z
LOCATION:
SUMMARY:Statistics and Data Science Colloquium: Regression Methods for Netw
ork Indexed Data: Modeling Occurrences of Burglary and Identifying Correla
tes of Injection Drug Use Cessation
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