fadjpdun: Adjusted p-Values for Dunnett-Based Graphical Approaches

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

Adjusted p-Values for Dunnett-Based Graphical Approaches

Description

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

Usage

fadjpdun(wgtmat, p, family = NULL, corr = 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.
corr	The correlation matrix that should be used for the parametric test. Can contain NAs for unknown correlations between families.

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.

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)
corr = matrix(c(1,0.5,NA,NA, 0.5,1,NA,NA,
                NA,NA,1,0.5, NA,NA,0.5,1),
              nrow = 4, byrow = TRUE)
fadjpdun(wgtmat, pvalues, family, corr)

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