论文标题
随机对照试验中匹配的配对设计的最佳性
Optimality of Matched-Pair Designs in Randomized Controlled Trials
论文作者
论文摘要
在随机对照试验（RCT）中，治疗通常是通过分层随机分配的。我表明，在所有分层的随机化方案中，概率为一半的所有单元，某个匹配的配对设计实现了估计平均治疗效果（ATE）的最大统计精度。在重要的特殊情况下，根据基线结果，最佳设计对。在基于10个RCT的数据集的仿真研究中，相对于原始设计，该设计平均降低了ATE估计器的标准误差10％，高达34％。
In randomized controlled trials (RCTs), treatment is often assigned by stratified randomization. I show that among all stratified randomization schemes which treat all units with probability one half, a certain matched-pair design achieves the maximum statistical precision for estimating the average treatment effect (ATE). In an important special case, the optimal design pairs units according to the baseline outcome. In a simulation study based on datasets from 10 RCTs, this design lowers the standard error for the estimator of the ATE by 10% on average, and by up to 34%, relative to the original designs.
