Estimating average causal effects under general interference, with application to a social network experiment

  title={Estimating average causal effects under general interference, with application to a social network experiment},
  author={Peter M. Aronow and Cyrus Samii},
  journal={The Annals of Applied Statistics},
This paper presents a randomization-based framework for estimating causal effects under interference between units, motivated by challenges that arise in analyzing experiments on social networks. The framework integrates three components: (i) an experimental design that defines the probability distribution of treatment assignments, (ii) a mapping that relates experimental treatment assignments to exposures received by units in the experiment, and (iii) estimands that make use of the experiment… 

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