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- W785924154 abstract "We consider the problem of how to assign treatment in a randomized experiment, when the correlation among the outcomes is informed by a network available pre-intervention. Working within the potential outcome causal framework, we develop a class of models that posit such a correlation structure among the outcomes, and a strategy for allocating treatment optimally, for the goal of minimizing the integrated mean squared error of the estimated average treatment effect. We provide insights into features of the optimal designs via an analytical decomposition of the mean squared error used for optimization. We illustrate how the proposed treatment allocation strategy improves on allocations that ignore the network structure, with extensive simulations." @default.
- W785924154 created "2016-06-24" @default.
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- W785924154 date "2015-07-03" @default.
- W785924154 modified "2023-09-27" @default.
- W785924154 title "Optimal design of experiments in the presence of network-correlated outcomes." @default.
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