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(w, G, p)

Arguments

w	The vector of initial weights for elementary hypotheses.
G	The initial transition matrix.
p	The raw p-values for elementary hypotheses.

Value

A matrix of adjusted p-values.

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)
fadjpbon(w, g, pvalues)

lrstat documentation built on Oct. 18, 2024, 9:06 a.m.