论文标题
关于与小型飞行员的Neyman分配的性能
On the Performance of the Neyman Allocation with Small Pilots
论文作者
论文摘要
Neyman分配用于许多实验设计论文中，通常认为研究人员可以访问大型试点研究。这可能是不现实的。为了了解Neyman分配的特性，我们在渐近框架中研究其行为，该框架的大小需要固定，即使主波的大小倾向于无穷大。我们的分析表明，与（非自适应）平衡随机化相比，Neyman分配可以导致具有渐近方差更高的ATE估计。特别是，当结果变量在治疗状态或表现出较高的峰度时，这种情况就会发生。我们提供了一系列经验例子，表明这种情况在实践中可能会出现。我们的结果表明，如果Neyman认为结果是同性恋或重型尾部，则没有小型飞行员的研究人员不应使用分配。最后，我们检查了一些通过模拟改善FNA的有限样品性能的潜在方法。
The Neyman Allocation is used in many papers on experimental design, which typically assume that researchers have access to large pilot studies. This may be unrealistic. To understand the properties of the Neyman Allocation with small pilots, we study its behavior in an asymptotic framework that takes pilot size to be fixed even as the size of the main wave tends to infinity. Our analysis shows that the Neyman Allocation can lead to estimates of the ATE with higher asymptotic variance than with (non-adaptive) balanced randomization. In particular, this happens when the outcome variable is relatively homoskedastic with respect to treatment status or when it exhibits high kurtosis. We provide a series of empirical examples showing that such situations can arise in practice. Our results suggest that researchers with small pilots should not use the Neyman Allocation if they believe that outcomes are homoskedastic or heavy-tailed. Finally, we examine some potential methods for improving the finite sample performance of the FNA via simulations.
