Optimal Design of Experiments on Connected Units with Application to Social Networks
研究了实验单元间存在连接时（如社交网络）如何设计实验，提出线性网络效应模型，证明最优设计不再需要平衡，并指出忽略网络效应会导致方差增大和偏差。
Summary When experiments are performed on social networks, it is difficult to justify the usual assumption of treatment–unit additivity, owing to the connections between actors in the network. We investigate how connections between experimental units affect the design of experiments on those experimental units. Specifically, where we have unstructured treatments, whose effects propagate according to a linear network effects model which we introduce, we show that optimal designs are no longer necessarily balanced; we further demonstrate how experiments which do not take a network effect into account can lead to much higher variance than necessary and/or a large bias. We show the use of this methodology in a very wide range of experiments in agricultural trials, and crossover trials, as well as experiments on connected individuals in a social network.