Causal Inference in the Presence of Interference

Neyman Seminar
Nov 29, 2017 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
A fundamental assumption usually made in causal inference is that of no interference between individuals (or units), i.e., the potential outcomes of one individual are assumed to be unaffected by the treatment assignment of other individuals. However, in many settings, this assumption obviously does not hold. For example, in infectious diseases, whether one person becomes infected depends on who...
Michael Hudgens, UNC-Chapel Hill