Nothing
`print.permutest.betadisper` <- function(x, digits = max(getOption("digits") - 2, 3),
...)
{
## uses code from stats:::print.anova by R Core Development Team
cat("\n")
writeLines(strwrap("Permutation test for homogeneity of multivariate dispersions\n"))
##cat("\n")
cat(howHead(x$control))
nc <- dim(x$tab)[2]
cn <- colnames(x$tab)
has.P <- substr(cn[nc], 1, 3) == "Pr("
zap.i <- 1:(if (has.P)
nc - 1
else nc)
i <- which(substr(cn, 2, 7) == " value")
i <- c(i, which(!is.na(match(cn, "F"))))
if (length(i))
zap.i <- zap.i[!(zap.i %in% i)]
tst.i <- i
if (length(i <- grep("Df$", cn)))
zap.i <- zap.i[!(zap.i %in% i)]
if (length(i <- grep("N.Perm$", cn)))
zap.i <- zap.i[!(zap.i %in% i)]
cat("\nResponse: Distances", sep = "\n")
printCoefmat(x$tab, digits = digits,
signif.stars = getOption("show.signif.stars"),
has.Pvalue = has.P, P.values = has.P, cs.ind = NULL,
zap.ind = zap.i, tst.ind = tst.i, na.print = "", ...)
if(!is.null(x$pairwise)) {
cat("\nPairwise comparisons:", sep = "\n")
writeLines(strwrap("(Observed p-value below diagonal,\npermuted p-value above diagonal)\n"))
n.grp <- length(x$groups)
mat <- matrix(NA, ncol = n.grp, nrow = n.grp)
colnames(mat) <- rownames(mat) <- x$groups
mat[lower.tri(mat)] <- x$pairwise$observed
mat <- t(mat)
mat[lower.tri(mat)] <- x$pairwise$permuted
printCoefmat(t(mat), na.print = "", digits = digits)
}
invisible(x)
}
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