评估两项多特征研究结果的可复制性
Assessing replicability of findings across two studies of multiple features
摘要：
重复性分析旨在确定在检查相同特征的独立研究中重复的发现。我们提供了强大的新的可复制性分析程序的两项研究FWER和FDR控制的可复制性索赔。建议的程序首先选择有前途的功能，从每个研究完全基于该研究，然后测试的可复制性，只有在两个研究中选择的功能。我们将一项研究中的零假设部分的插件估计纳入另一项研究所选的假设中。由于一项研究中的零值在另一项研究中所选特征中的比例通常很小，因此功率增益可能非常显著。我们提供了理论上的保证，控制适当的错误率，以及模拟，展示了优良的功率特性的建议的程序。我们证明了我们的程序的实用性，从两个应用领域的真实数据的例子：行为遗传学和微阵列研究。
英文摘要：
Replicability analysis aims to identify the findings that replicated across independent studies that examine the same features. We provide powerful novel replicability analysis procedures for two studies for FWER and for FDR control on the replicability claims. The suggested procedures first select the promising features from each study solely based on that study, and then test for replicability only the features that were selected in both studies. We incorporate the plug-in estimates of the fraction of null hypotheses in one study among the selected hypotheses by the other study. Since the fraction of nulls in one study among the selected features from the other study is typically small, the power gain can be remarkable. We provide theoretical guarantees for the control of the appropriate error rates, as well as simulations that demonstrate the excellent power properties of the suggested procedures. We demonstrate the usefulness of our procedures on real data examples from two application fields: behavioural genetics and microarray studies.
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