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错误发现率的稳健估计

Robust estimation of the false discovery rate.

作者信息

Pounds Stan, Cheng Cheng

机构信息

Department of Biostatistics, St. Jude Children's Research Hospital 332 N. Lauderdale Street, Memphis, TN 38135, USA.

出版信息

Bioinformatics. 2006 Aug 15;22(16):1979-87. doi: 10.1093/bioinformatics/btl328. Epub 2006 Jun 15.

Abstract

MOTIVATION

Presently available methods that use p-values to estimate or control the false discovery rate (FDR) implicitly assume that p-values are continuously distributed and based on two-sided tests. Therefore, it is difficult to reliably estimate the FDR when p-values are discrete or based on one-sided tests.

RESULTS

A simple and robust method to estimate the FDR is proposed. The proposed method does not rely on implicit assumptions that tests are two-sided or yield continuously distributed p-values. The proposed method is proven to be conservative and have desirable large-sample properties. In addition, the proposed method was among the best performers across a series of 'real data simulations' comparing the performance of five currently available methods.

AVAILABILITY

Libraries of S-plus and R routines to implement the method are freely available from www.stjuderesearch.org/depts/biostats.

摘要

动机

目前可用的使用p值来估计或控制错误发现率(FDR)的方法隐含地假设p值是连续分布的且基于双侧检验。因此,当p值是离散的或基于单侧检验时,很难可靠地估计FDR。

结果

提出了一种简单且稳健的估计FDR的方法。所提出的方法不依赖于检验是双侧的或产生连续分布的p值的隐含假设。所提出的方法被证明是保守的并且具有理想的大样本性质。此外,在一系列比较五种当前可用方法性能的“真实数据模拟”中,所提出的方法是表现最佳的方法之一。

可用性

可从www.stjuderesearch.org/depts/biostats免费获得用于实现该方法的S-plus和R程序库。

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