Adjusted p-Values for Dunnett-Based Graphical Approaches

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.

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.

Author

Kaifeng Lu, kaifenglu@gmail.com

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)
#>      [,1]       [,2]       [,3]       [,4]
#> [1,] 0.02 0.01000000 0.02772937 0.02772937
#> [2,] 0.04 0.02772937 0.04000000 0.04000000