Implementing false discovery rate control: increasing your power
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Abstract
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…
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Topics
Keywords
- Bonferroni correction
- False discovery rate
- Multiple comparisons problem
- Type I and type II errors
- Computer science
- Statistical power
- Statistics
- Control (management)
UN Sustainable Development Goals
- Peace, Justice and strong institutions
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