Jan 22, 2019 11:00am to 12:30pm
1011 Evans Hall
Happening As Scheduled
Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed covariates. It is often believed that the more covariates we condition on, the more plausible this unconfoundedness assumption is. This belief has had a huge...
Speakers: Peng Ding (Speaker - Featured)