two.stage {mutoss}

A p-value procedure which controls the FDR for independent test statistics.

Description

A p-value procedure which controls the FDR for independent test statistics.

Usage

two.stage(pValues, alpha)

Arguments

pValues

A numeric vecor of p-values.

alpha

The FDR error rate to control.

Details

In the Benjamini-Krieger-Yekutieli two-stage procedure the linear step-up procedure is used in stage one to estimate m0 which is re-plugged in a linear step-up. This procedure is more powerful then non-adaptive procedures, while still controlling the FDR. On the other hand, error control is not guaranteed under dependence in which case more conservative procedures should be used (e.g. BH).

Value

A list containing:

rejected

A logical vector indicating which hypotheses are rejected

criticalValues

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

adjPValues

A numeric vector containing adjusted p-values.

pi0

An estimate of the proportion of true null hypotheses among all hypotheses (pi0=m0/m).

errorControl

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

Author(s)

JonathanRosenblatt

Examples

pvals<- runif(100)^2
two.stage(pvals, 0.1)