Improving the statistical power of economic experiments using adaptive designs
介绍了如何在经济实验中使用自适应两阶段设计来同时检验多个假设，从而提高统计功效，并通过模拟和两个实际数据集展示了该方法在保持总体一类错误控制的同时减少样本量的潜力。
Abstract An important issue for many economic experiments is how the experimenter can ensure sufficient power in order to reject one or more hypotheses. The paper illustrates how methods for testing multiple hypotheses simultaneously in adaptive, two-stage designs can be used to improve the power of economic experiments. We provide a concise overview of the relevant theory and illustrate the method in three different applications. These include a simulation study of a hypothetical experimental design, as well as illustrations using two data sets from previous experiments. The simulation results highlight the potential for sample size reductions, maintaining the power to reject at least one hypothesis while ensuring strong control of the overall Type I error probability.