Implementing false discovery rate control: increasing your power

被引:816
作者
Verhoeven, KJF
Simonsen, KL
McIntyre, LM
机构
[1] Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA
[2] Purdue Univ, Dept Stat, W Lafayette, IN 47907 USA
关键词
D O I
10.1111/j.0030-1299.2005.13727.x
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Popular procedures to control the chance of making type I errors when multiple statistical tests are performed come at a high cost: a reduction in power. As the number of tests increases, power for an individual test may become unacceptably low. This is a consequence of minimizing the chance of making even a single type I error, which is the aim of, for instance, the Bonferroni and sequential Bonferroni procedures. An alternative approach, control of the false discovery rate (FDR), has recently been advocated for ecological studies. This approach aims at controlling the proportion of significant results that are in fact type I errors. Keeping the proportion of type I errors low among all significant results is a sensible, powerful, and easy-to-interpret way of addressing the multiple testing issue. To encourage practical use of the approach, in this note we illustrate how the proposed procedure works, we compare it to more traditional methods that control the familywise error rate, and we discuss some recent useful developments in FDR control.
引用
收藏
页码:643 / 647
页数:5
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