|Title||The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing.|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Cao, Hongyuan, Wenguang Sun, and Michael R. Kosorok|
In single hypothesis testing, power is a non-decreasing function of type I error rate; hence it is desirable to test at the nominal level exactly to achieve optimal power. The puzzle lies in the fact that for multiple testing, under the false discovery rate paradigm, such a monotonic relationship may not hold. In particular, exact false discovery rate control may lead to a less powerful testing procedure if a test statistic fails to fulfil the monotone likelihood ratio condition. In this article, we identify different scenarios wherein the condition fails and give caveats for conducting multiple testing in practical settings.
|Original Publication||The optimal power puzzle: Scrutiny of the monotone likelihood ratio assumption in multiple testing.|
|PubMed Central ID||PMC3984571|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States|
The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing.