IHW

Description

Independent hypothesis weighting (IHW) is a multiple testing procedure that increases power compared to the method of Benjamini and Hochberg by assigning data-driven weights to each hypothesis. The input to IHW is a two-column table of p-values and covariates. The covariate can be any continuous-valued or categorical variable that is thought to be informative on the statistical properties of each hypothesis test, while it is independent of the p-value under the null hypothesis.

Code

Code metrics have not been computed for this package yet.

Topics

Depended on by (10)

People

• Nikos Ignatiadis author maintainer
• Wolfgang Huber author