Elements of estimation theory for causal effects in the presence of network interference
DL Sussman, EM Airoldi - arXiv preprint arXiv:1702.03578, 2017 - arxiv.org
Randomized experiments in which the treatment of a unit can affect the outcomes of other
units are becoming increasingly common in healthcare, economics, and in the social and
information sciences. From a causal inference perspective, the typical assumption of no
interference becomes untenable in such experiments. In many problems, however, the
patterns of interference may be informed by the observation of network connections among
the units of analysis. Here, we develop elements of optimal estimation theory for causal …
units are becoming increasingly common in healthcare, economics, and in the social and
information sciences. From a causal inference perspective, the typical assumption of no
interference becomes untenable in such experiments. In many problems, however, the
patterns of interference may be informed by the observation of network connections among
the units of analysis. Here, we develop elements of optimal estimation theory for causal …
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