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Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures

机译:试验实验数据中的异构治疗效果:虚假发现风险和校正程序

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摘要

We review the statistical models applied to test for heterogeneous treatment effects in the recent empirical literature, with a particular focus on data from randomized field experiments. We show that testing for heterogeneous treatment effects is highly common, and likely to result in a large number of false discoveries when conventional standard errors are applied. We demonstrate that applying correction procedures developed in the statistics literature can fully address this issue, and discuss the implications of multiple testing adjustments for power calculations and experimental design.
机译:我们回顾了最近的经验文献中用于检验异质性治疗效果的统计模型,特别关注了来自随机现场实验的数据。我们表明,异质处理效果的测试非常普遍,当应用常规标准错误时,很可能导致大量错误发现。我们证明了应用统计文献中开发的校正程序可以完全解决此问题,并讨论了多种测试调整对功率计算和实验设计的影响。

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