论文标题
实验的有效平衡治疗分配
Efficient Balanced Treatment Assignments for Experimentation
论文作者
论文摘要
在这项工作中，我们将平衡治疗分配的问题重新构架为测试和控制单元之间的两样本测试的优化。使用此镜头，我们提供了一种分配算法，该算法相对于Friedman和Rafsky（1979）的最小生成树测试是最佳的。该分配对治疗组的分配可以在多项式时间内精确地进行。我们根据确定点过程的设计最可能的元素提供了对该过程的概率解释，该过程接受了对设计的概率解释。我们提供了一种新颖的估计表达式作为转导推断，并显示了设计中使用的树结构如何在调整估计仪中使用。我们以仿真研究结论，证明了我们方法的功效提高。
In this work, we reframe the problem of balanced treatment assignment as optimization of a two-sample test between test and control units. Using this lens we provide an assignment algorithm that is optimal with respect to the minimum spanning tree test of Friedman and Rafsky (1979). This assignment to treatment groups may be performed exactly in polynomial time. We provide a probabilistic interpretation of this process in terms of the most probable element of designs drawn from a determinantal point process which admits a probabilistic interpretation of the design. We provide a novel formulation of estimation as transductive inference and show how the tree structures used in design can also be used in an adjustment estimator. We conclude with a simulation study demonstrating the improved efficacy of our method.
