Statistics Colloquium: Michael Hudgens
11:30 am–12:30 pm Jones 303
Michael Hudgens, Department of Biostatistics, University of North Carolina at Chapel Hill
Title: Causal Inference with Interference
Abstract: 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 may depend on who else in the population is vaccinated. In this talk we will discuss recent approaches to assessing treatment effects in the presence of interference.