mantelTest: Mantel's Permutation Test

Description

Mantel's permutation test based on Pearson's correlation coefficient to evaluate the association between two distance square matrices.

Usage

mantelTest(m1, m2, nperm = 999, alternative = "greater", 
	graph = TRUE, main = "Mantel's test", xlab = "Correlation", ...)

Arguments

an object of class "matrix" or "dist", containing distances among n individuals.

nperm

the number of matrix permutations.

alternative

a character specifying the alternative hypothesis. It must be one of "greater" (default), "two.sided" or "less".

graph

logical; if TRUE (default), the empirical distribution is plotted.

main

opitional; a character describing the title of the graphic.

xlab

opitional; a character describing the x-axis label.

...

further graphical arguments. See par.

Value

A list of
correlationnumeric; the observed Pearson's correlation between m1 and m2.
p.valuenumeric; the empirical p-value of the permutation test.
alternativecharacter; the alternative hypothesis used to compute p.value.
nullcornumeric vector containing randomized values of correlation, i.e., under the null hypothesis that the true correlation is equal to zero.

References

Mantel, N. (1967). The detection of disease clustering and a generalized regression approach. Cancer Research, 27:209--220.

Examples

Run this code

# Distances between garlic cultivars
data(garlicdist)
garlicdist

# Tocher's clustering
garlic <- tocher(garlicdist)
garlic

# Cophenetic distances
coph <- cophenetic(garlic)
coph

# Mantel's test
mantelTest(garlicdist, coph, 
	xlim = c(-1, 1))

# End (Not run)