Dynamic e-closure controls stopped and supremum FDR for growing hypothesis families with continuing evidence, and shows coherent admissible pointwise mergers require one global weight sequence.
A Uniform Improvement of the Benjamini-Hochberg Procedure via e-Closure
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abstract
This paper presents closed BH, a uniform improvement of the False Discovery Rate controlling method of Benjamini and Hochberg (BH). Closed BH is valid under the same assumption of Positive Regression Dependency on a Subset (PRDS) as BH, but also under an alternative and weaker minimal sufficient condition. As a uniform improvement, closed BH never rejects fewer hypotheses than BH, but it may reject quite a few more. An increase in power is observed especially when the number of false null hypotheses is large. The novel method is constructed using the e-Closure principle, a recently derived general principle for multiple testing. The method is implemented in the eClosure package in R.
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Dynamic $e$-closure for online hypotheses with any-time-valid evidence: closure principles and projective mergers
Dynamic e-closure controls stopped and supremum FDR for growing hypothesis families with continuing evidence, and shows coherent admissible pointwise mergers require one global weight sequence.