The effect of correlation in false discovery rate estimation
The effect of correlation in false discovery rate estimation
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DOI：
10.1093/biomet/asq075
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发表时间：
2011-03-01
期刊：
影响因子：
2.7
通讯作者：
Lin, Xihong
中科院分区：
文献类型：
--
作者：
Schwartzman, Armin;Lin, Xihong
本文的目的是量化的假发现率分析的相关性的影响。具体来说，我们推导出近似的平均值，方差，分布和分位数的标准错误发现率估计任意相关的数据。这是使用负二项模型的错误发现的数量，其中的参数是从数据中发现的经验。我们表明，相关性可能会增加的偏差和方差的估计大幅相对于独立的情况下，在某些情况下，如可交换的相关性结构，估计不一致的测试数量变得很大。
The objective of this paper is to quantify the effect of correlation in false discovery rate analysis. Specifically, we derive approximations for the mean, variance, distribution and quantiles of the standard false discovery rate estimator for arbitrarily correlated data. This is achieved using a negative binomial model for the number of false discoveries, where the parameters are found empirically from the data. We show that correlation may increase the bias and variance of the estimator substantially with respect to the independent case, and that in some cases, such as an exchangeable correlation structure, the estimator fails to be consistent as the number of tests becomes large.