Researchers conducting randomized trials have increasingly shifted focus from the average treatment effect to understanding moderators of treatment effects. Current methods for exploring moderation focus on model selection and hypothesis tests. At the same time, recent developments in the design of randomized trials have argued for the need for population‐based recruitment in order to generalize well. In this paper, we show that a different population‐based recruitment strategy can be implemented to increase the precision of estimates of treatment effect moderators, and we explore the trade‐offs between optimal designs for the average treatment effect and moderator effects.

中文翻译：

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超越ATE的一般化：设计随机试验以了解治疗效果的异质性

进行随机试验的研究人员越来越多地将注意力从平均治疗效果转移到了理解治疗效果的调节剂上。当前探索适度性的方法侧重于模型选择和假设检验。同时，随机试验设计的最新进展表明，有必要进行以人群为基础的招募，以便将其普遍化。在本文中，我们表明可以采用不同的基于人群的招聘策略来提高治疗效果调节剂的估算精度，并且我们探索了平均治疗效果和调节剂效果的最佳设计之间的权衡。