BY: Benjamini-Yekutieli (2001) step-up procedure

Description Usage Arguments Details Value Author(s) References Examples

Description

The Benjamini-Yekutieli step-up procedure is applied to pValues. The procedure ensures FDR control for any dependency structure.

Usage

1
BY(pValues, alpha, silent=FALSE)

Arguments

pValues

The used unadjusted pValues.

alpha

The level at which the FDR shall be controlled.

silent

If true any output on the console will be suppressed.

Details

The critical values of the Benjamini-Yekutieli (BY) procedure are calculated by replacing the alpha of the Benjamini-Hochberg procedure by alpha/sum(1/1:m)), i.e., c(i)=i*alpha/(m*(sum(1/1:m))) for i=1,...,m. For large number m of hypotheses the critical values of the BY procedure and the BH procedure differ by a factor log(m). Benjamini and Yekutieli (2001) showed that this step-up procedure controls the FDR at level alpha*m/m0 for any dependency structure among the test statistics.

Value

A list containing:

adjPValues

A numeric vector containing the adjusted pValues

criticalValues

A numeric vector containing critical values used in the step-up-down test

rejected

A logical vector indicating which hypotheses are rejected

errorControl

A Mutoss S4 class of type errorControl, containing the type of error controlled by the function and the level alpha.

Author(s)

WerftWiebke

References

Benjamini, Y. and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics, 29(4):1165-1188.

Examples

1
2
3
4
alpha <- 0.05
p <-c(runif(10, min=0, max=0.01), runif(10, min=0.9, max=1))
result <- BY(p, alpha)
result <- BY(p, alpha, silent=TRUE)


Search within the mutoss package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.