gbonf.cv: Critical Value for the generalized Bonferroni Procedure...

Description Usage Arguments Value Author(s) See Also Examples

View source: R/kFWER_adjP.R

Description

The function for computing the critical value based on number of hypotheses m, fold k and significant level α.

Usage

1
gbonf.cv(m, k, alpha)

Arguments

m

number of hypotheses to be tested.

k

number of allowed type 1 errors in k-FWER controls.

alpha

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

Value

A numeric vector of the adjusted p-values (of the same length as p) if make.decision = FALSE, or a list including original p-values, adjusted p-values and decision rules if make.decision = TRUE.

Author(s)

Yalin Zhu

See Also

gbonf.p.adjust, p.adjust, Sidak.p.adjust.

Examples

1
2
p <- c(0.031,0.023,0.029,0.005,0.031,0.000,0.874,0.399,0.293,0.077)
gbonf.cv(m=length(p), k=2)

allenzhuaz/MHTmult documentation built on June 1, 2017, 5:22 p.m.