A direct approach to false discovery rates
A direct approach to false discovery rates
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DOI：
10.1111/1467-9868.00346
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发表时间：
2002-01-01
影响因子：
5.8
通讯作者：
Storey, JD
中科院分区：
文献类型：
--
作者：
Storey, JD
多假设检验涉及防止比单假设检验复杂得多的错误。虽然我们通常控制单假设检验的I类错误率，但多假设检验的复合错误率是受控的。例如，控制错误发现率FDR传统上涉及基于观察到的数据的复杂的顺序p值拒绝方法。而顺序p值方法固定的错误率，并估计其相应的拒绝区域，我们提出了相反的方法，我们固定的拒绝区域，然后估计其相应的错误率。这种新方法提供了更高的适用性，准确性和功率。我们将该方法应用于阳性假发现率pFDR和FDR，并为其益处提供证据。结果表明，pFDR可能是FDR上的感兴趣量。还讨论了q值的计算，p值的pFDR模拟，这消除了像传统上那样预先设置错误率的需要。一些简单的数值例子表明，这种新的方法可以产生超过8倍的功率相比，Benjamini-Hochberg FDR方法。
Multiple-hypothesis testing involves guarding against much more complicated errors than single-hypothesis testing. Whereas we typically control the type I error rate for a single-hypothesis test, a compound error rate is controlled for multiple-hypothesis tests. For example, controlling the false discovery rate FDR traditionally involves intricate sequential p-value rejection methods based on the observed data. Whereas a sequential p-value method fixes the error rate and estimates its corresponding rejection region, we propose the opposite approach-we fix the rejection region and then estimate its corresponding error rate. This new approach offers increased applicability, accuracy and power. We apply the methodology to both the positive false discovery rate pFDR and FDR, and provide evidence for its benefits. It is shown that pFDR is probably the quantity of interest over FDR. Also discussed is the calculation of the q-value, the pFDR analogue of the p-value, which eliminates the need to set the error rate beforehand as is traditionally done. Some simple numerical examples are presented that show that this new approach can yield an increase of over eight times in power compared with the Benjamini-Hochberg FDR method.