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Implementing false discovery rate control: increasing your power
Author(s) -
Verhoeven Koen J.F.,
Simonsen Katy L.,
McIntyre Lauren M.
Publication year - 2005
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/j.0030-1299.2005.13727.x
Subject(s) - bonferroni correction , false discovery rate , multiple comparisons problem , type i and type ii errors , computer science , statistical power , statistics , control (management) , word error rate , statistical hypothesis testing , mathematics , artificial intelligence , biology , gene , biochemistry
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.