最小适应性BH方法：对Benjamini和Hochberg方法的微小但统一的改进。

Minimally adaptive BH: A tiny but uniform improvement of the procedure of Benjamini and Hochberg.

作者信息

Solari Aldo, Goeman Jelle J

机构信息

Department of Economics, Management and Statistics, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, 20126 Milan, Italy.

Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Postzone S5-P, Postbus 9600, 2300 RC Leiden, The Netherlands.

出版信息

Biom J. 2017 Jul;59(4):776-780. doi: 10.1002/bimj.201500253. Epub 2016 May 18.

DOI:10.1002/bimj.201500253

PMID:27192178

Abstract

We define an adaptive procedure for control of the false discovery rate that is uniformly more powerful than the procedure of Benjamini and Hochberg. The power gain is tiny, however, and only appreciable for small numbers of hypotheses. We illustrate the new method with the case of two hypotheses, for which so far no procedure was known that controls false discovery rate but not also familywise error rate under positive dependence.

摘要

我们定义了一种用于控制错误发现率的自适应程序，该程序比Benjamini和Hochberg的程序具有更强的一致性功效。然而，功效增益很小，并且仅在假设数量较少时才明显。我们以两个假设的情况为例说明了这种新方法，到目前为止，还没有已知的程序可以在正相关下控制错误发现率但不控制族系错误率。