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CIRG Seminar: Alexander Volfovsky
October 7, 2016 @ 12:00 pm - 2:00 pm
Alexander Volfovsky, Assistant Professor of Statistical Science at Duke University, will be the second speaker in the Causal Inference Research Group 2016 Fall Seminar Series.
Room: Bondurant Hall G010
Title: Causal inference in the presence of networks: randomization and observation
Much of classical causal analysis relies on notions of independence.
However, modern datasets on disease prevalence, social development, online advertising and business transactions come equipped with information on a network that links the units together, rendering these notions implausible.
When designing randomized experiments, scientists must control for network interference and homophily in order to guarantee the theoretical properties of their estimators.
Studying the direct treatment effect in networks, we describe a new class of randomizations that can guarantee unbiasedness and control the variance of the estimator.
In situations where an experiment cannot be performed, causal analysis requires the use of matching techniques in order to protect against bias due to a lack of balance between treated and control units.
We provide examples of the complications that arise when information about the network is disregarded and develop a matching technique that extends classical propensity scores to the realm of networks.