Seminar

2014 Apr 03

BUStatPrSem: Scott Robertson

4:00pm to 5:00pm

Location: 

MCS 148
Continuous Time Perpetuities and the Time Reversal of Diffusions
2014 Apr 28

BrownCSSem: Florentina Bunea

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Convex Banding of High Dimensional Covariance Matrices
2014 Oct 06

BrownCSSem: David Meltzer

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Redesign of Care for Patients at High Risk of Hospitalization in a Reforming U.S. Healthcare System: Rationale for a CMMI Innovation Challenge Project
2014 Dec 08

BrownCSSem: Elizabeth Stuart

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Propensity Score Methods in the Context of Covariate Measurement Error
2015 Feb 05

BUStatPrSem: Eric Fox

4:00pm to 5:00pm

Location: 

MCS 148
Estimation and Inference for Self-Exciting Point Processes, with Applications to Social Networks and Earthquake Seismology
2015 Apr 08

HBSDigitalSem: Susan Athey

12:00pm to 1:30pm

Location: 

Cotting House, 1st floor conference room, HBS campus
Title: Aggregators, Social Media, and News Consumption Abstract: In a series of studies, we explore the ways in which aggregators and intermediaries affect the consumption of news on the internet. We analyze several natural experiments involving the Google News aggregator, showing that Google News redistributes news consumption away from large outlets and towards small outlets, and decreases user loyalty to their favorite outlets. We find evidence that Google News increases overall news consumption, consistent with the theory that it reduces search costs and helps users discover stories and... Read more about HBSDigitalSem: Susan Athey
2013 Oct 07

BrownCSSem: Brent A. Johnson

3:30pm to 5:00pm

Location: 

Room 245, 121 South Main Street, Providence
Weighted Logrank Statistics for Marked Endpoints with Application to the Analysis of Lifetime Medical Cost
2014 Feb 27

BUStatPrSem: Jeremy Achin

4:00pm to 5:00pm

Location: 

MCS 148
Applied Data Science: Extracting Maximum Value from Real-World Data

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