MBY.p.adjust {MHTdiscrete}

The adjusted p-values for Modified Benjamini-Yekutieli (BY) step-up FDR controlling procedure.

Description

The function for calculating the adjusted p-values based on original available p-values and all attaianble p-values.

Usage

MBY.p.adjust(p, p.set, alpha, make.decision)

Arguments

p

numeric vector of p-values (possibly with NAs). Any other R is coerced by as.numeric. Same as in p.adjust.

p.set

a list of numeric vectors, where each vector is the vector of all attainable p-values containing the available p-value for the corresponding hypothesis.

alpha

significant level used to compare with adjusted p-values to make decisions, the default value is 0.05.

make.decision

logical; if TRUE, then the output include the decision rules compared adjusted p-values with significant level \alpha

Value

A numeric vector of the adjusted p-values (of the same length as p).

Author(s)

Yalin Zhu

References

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

See Also

MBH.p.adjust, MBL.p.adjust

Examples

p <- c(pbinom(1,8,0.5),pbinom(1,5,0.75),pbinom(1,6,0.6))
p.set <-list(pbinom(0:8,8,0.5),pbinom(0:5,5,0.75),pbinom(0:6,6,0.6))
MBY.p.adjust(p,p.set)