Weighted Bonferroni-test

Usage

bonferroni.test(
  pvalues,
  weights,
  alpha = 0.05,
  adjPValues = TRUE,
  verbose = FALSE,
  ...
)

Arguments

pvalues: A numeric vector specifying the p-values.
weights: A numeric vector of weights.
alpha: A numeric specifying the maximal allowed type one error rate. If adjPValues==TRUE (default) the parameter alpha is not used.
adjPValues: Logical scalar. If TRUE (the default) an adjusted p-value for the weighted Bonferroni-test is returned. Otherwise if adjPValues==FALSE a logical value is returned whether the null hypothesis can be rejected.
verbose: Logical scalar. If TRUE verbose output is generated.
...: Further arguments possibly passed by gMCP which will be used by other test procedures but not this one.

Examples


bonferroni.test(pvalues=c(0.1,0.2,0.05), weights=c(0.5,0.5,0))
#> [1] 0.2
bonferroni.test(pvalues=c(0.1,0.2,0.05), weights=c(0.5,0.5,0), adjPValues=FALSE)
#> [1] FALSE