gMCP (version 0.6-5)

generateTest: generateTest

Description

generates a test function for the multiple comparison procedure with correlated test statistics defined by a graph

Usage

generateTest(g, w, c, al)

Arguments

g

graph defined as a matrix, each element defines how much of the local alpha reserved for the hypothesis corresponding to its row index is passed on to the hypothesis corresponding to its column index

w

vector of weights, defines how much of the overall alpha is initially reserved for each elementary hypothesis

c

correlation matrix defining pairwise correlations between the elementary hypotheses. Unknown values can be set to NA.

al

overall alpha level at which the family error is controlled

Value

• Returns a function that will take a vector of z-scores to which the test will be applied. This function in turn will return a boolean vector with elements false if the particular elementary hypothesis can not be rejected and true otherwise.

Details

Correlation structure needs to possess block structure (without overlapping blocks) otherwise multcomp will throw an exception as NA correlations are fed to the multivariate normal distribution

References

Bretz F, Maurer W, Brannath W, Posch M; (2008) - A graphical approach to sequentially rejective multiple testing procedures. - Stat Med - 28/4, 586-604 Bretz F, Posch M, Glimm E, Klinglmueller F, Maurer W, Rohmeyer K; (2011) - Graphical approaches for multiple endpoint problems using weighted Bonferroni, Simes or parametric tests - to appear

Examples

## Define some graph as matrix
 g <- matrix(c(0,0,1,0,
               0,0,0,1,
               0,1,0,0,
               1,0,0,0), nrow = 4,byrow=TRUE)
 ## Choose weights
 w <- c(.5,.5,0,0)
 ## Some correlation (upper and lower first diagonal 1/2)
 c <- diag(4)
 c[1:2,3:4] <- NA
 c[3:4,1:2] <- NA
 c[1,2] <- 1/2
 c[2,1] <- 1/2
 c[3,4] <- 1/2
 c[4,3] <- 1/2

 ## Test function for further use:
 myTest <- generateTest(g,w,c,.05)
 myTest(c(3,2,1,2))