fadjpsim: Adjusted p-Values for Simes-Based Graphical Approaches

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

Adjusted p-Values for Simes-Based Graphical Approaches

Description

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

Usage

fadjpsim(wgtmat, p, family = NULL)

Arguments

wgtmat	The weight matrix for intersection hypotheses.
p	The raw p-values for elementary hypotheses.
family	The matrix of family indicators for elementary hypotheses.

Value

A matrix of adjusted p-values.

Author(s)

Kaifeng Lu, [e-mail]

References

Frank Bretz, Martin Posch, Ekkehard Glimm, Florian Klinglmueller, Willi Maurer, and Kornelius Rohmeyer. Graphical approach for multiple comparison procedures using weighted Bonferroni, Simes, or parameter tests. Biometrical Journal. 2011; 53:894-913.

Kaifeng Lu. Graphical approaches using a Bonferroni mixture of weighted Simes tests. Statistics in Medicine. 2016; 35:4041-4055.

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)

family = matrix(c(1,1,0,0,0,0,1,1), nrow=2, ncol=4, byrow=TRUE)
fadjpsim(wgtmat, pvalues, family)

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