Nothing
dunnett.test <-
function (Z = Z, select = rep(1, length(Z)))
{
if(sum(is.na(Z))>0){stop("No missing values allowed in Z")}
treats <- length(Z)
hyp.comb <- list(NULL)
nhyp.comb <- vector(length = treats)
for (i in 1:treats) {
comb.dat <- combn(1:treats, i)
hyp.comb[[i]] <- comb.dat
nhyp.comb[i] <- ncol(hyp.comb[[i]])
rownames(hyp.comb[[i]]) <- 1:i
hypcol <- NULL
for (j in 1:nhyp.comb[i]) {
ihypcol <- paste("H", paste(hyp.comb[[i]][, j], collapse = ""),
sep = "")
hypcol <- append(hypcol, ihypcol)
}
colnames(hyp.comb[[i]]) <- hypcol
}
pdunnett.test <- list(NULL)
zscores <- list(NULL)
int_dunnett <- function(x, z, k) {
((pnorm(sqrt(2) * z + x))^k) * dnorm(x)
}
for (i in 1:treats) {
ptest <- NULL
if (select[i] == 0) {
Z[i] <- -Inf
}
for (j in 1:nhyp.comb[i]) {
kselect <- sum(select[c(hyp.comb[[i]][, j])])
Zmax <- max(Z[c(hyp.comb[[i]][, j])])
if (kselect == 0) {
dunnet_integral <- 0
F_Zmax <- 1
}
else {
dunnett_integral <- integrate(int_dunnett, -Inf,
Inf, z = Zmax, k = kselect)
F_Zmax <- 1 - dunnett_integral$value
}
ptest <- append(ptest, F_Zmax)
}
pdunnett.test[[i]] <- matrix(ptest, nrow = 1, ncol = length(ptest))
colnames(pdunnett.test[[i]]) <- colnames(hyp.comb[[i]])
rownames(pdunnett.test[[i]]) <- 1
zscores[[i]] <- qnorm(1 - pdunnett.test[[i]])
}
list(pvalues = pdunnett.test, zscores = zscores, hyp.comb = hyp.comb)
}
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