关于基因表达数据多重检验中强控制的置换程序
On Permutation Procedures for Strong Control in Multiple Testing with Gene Expression Data.
作者信息
Rempala Grzegorz A, Yang Yuhong
机构信息
Department of Biostatistics and Cancer Research Center, Georgia Health Sciences University,
School of Statistics, University of Minnesota,
出版信息
Stat Interface. 2013;6(1). doi: 10.4310/SII.2013.v6.n1.a8.
Abstract
We consider two popular, permutation-based, step-down procedures of -values adjustment in multiple testing problems known as min and max and intended for strong control of the family-wise error rate, under the so-called subset pivotality property (SPP). We examine key but subtle issues involved in ascertaining validity of these methods, and also introduce a new, slightly narrower notion of strong control which ensures proper bounds on the family-wise error rate in min and max without SPP.
摘要
我们考虑了多重检验问题中两种流行的、基于排列的逐步下调p值调整程序，分别称为minP和maxP，旨在在所谓的子集枢轴性属性（SPP）下严格控制家族性错误率。我们研究了确定这些方法有效性所涉及的关键但微妙的问题，并引入了一种新的、稍窄的严格控制概念，该概念可确保在没有SPP的情况下，minP和maxP中的家族性错误率有适当的界限。
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