bonferroni.trimmed.simes.test: Trimmed Simes test for intersections of two hypotheses and...

In gMCP: Graph Based Multiple Comparison Procedures

Trimmed Simes test for intersections of two hypotheses and otherwise weighted Bonferroni-test

Description

Trimmed Simes test for intersections of two hypotheses and otherwise weighted Bonferroni-test

Usage

bonferroni.trimmed.simes.test(
  pvalues,
  weights,
  alpha = 0.05,
  adjPValues = FALSE,
  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 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.

References

Brannath, W., Bretz, F., Maurer, W., & Sarkar, S. (2009). Trimmed Weighted Simes Test for Two One-Sided Hypotheses With Arbitrarily Correlated Test Statistics. Biometrical Journal, 51(6), 885-898.

Examples

bonferroni.trimmed.simes.test(pvalues=c(0.1,0.2,0.05), weights=c(0.5,0.5,0))
bonferroni.trimmed.simes.test(pvalues=c(0.1,0.2,0.05), weights=c(0.5,0.5,0), adjPValues=FALSE)

gMCP documentation built on May 29, 2024, 9:37 a.m.