fadjpbon: Adjusted p-Values for Bonferroni-Based Graphical Approaches

In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond

Adjusted p-Values for Bonferroni-Based Graphical Approaches

Description

Obtains the adjusted p-values for graphical approaches using weighted Bonferroni tests.

Usage

fadjpbon(p, wgtmat = NULL)

Arguments

p	The raw p-values for elementary hypotheses.
wgtmat	A list containing the weight matrix and the indicator matrix for intersection hypotheses. If NULL, equal weights are assigned within each intersection hypothesis.

Value

A list with the following components:

• inthyp: The indicator matrix for the intersection hypotheses.

• pinter: The local p-values for the intersection hypotheses.

• padj: The adjusted p-values for the elementary hypotheses.

Author(s)

Kaifeng Lu, [e-mail]

References

Frank Bretz, Willi Maurer, Werner Brannath and Martin Posch. A graphical approach to sequentially rejective multiple test procedures. Statistics in Medicine. 2009; 28:586-604.

Examples

pvalues <- matrix(c(0.01,0.005,0.015,0.022, 0.02,0.015,0.010,0.023),
                  nrow=2, ncol=4, byrow=TRUE)
w <- c(0.5,0.5,0,0)
G <- matrix(c(0,0,1,0,0,0,0,1,0,1,0,0,1,0,0,0),
            nrow=4, ncol=4, byrow=TRUE)
wgtmat <- fwgtmat(w,G)
fadjpbon(pvalues, wgtmat)

lrstat documentation built on Aug. 25, 2026, 5:07 p.m.