Description Usage Arguments Details Value Note Author(s) References See Also Examples
Function mantel
finds the Mantel statistic as a matrix
correlation between two dissimilarity matrices, and function
mantel.partial
finds the partial Mantel statistic as the
partial matrix correlation between three dissimilarity matrices. The
significance of the statistic is evaluated by permuting rows and
columns of the first dissimilarity matrix.
1 2 3 4  mantel(xdis, ydis, method="pearson", permutations=999, strata = NULL,
na.rm = FALSE, parallel = getOption("mc.cores"))
mantel.partial(xdis, ydis, zdis, method = "pearson", permutations = 999,
strata = NULL, na.rm = FALSE, parallel = getOption("mc.cores"))

xdis, ydis, zdis 
Dissimilarity matrices or a 
method 
Correlation method, as accepted by 
permutations 
a list of control values for the permutations
as returned by the function 
strata 
An integer vector or factor specifying the strata for permutation. If supplied, observations are permuted only within the specified strata. 
na.rm 
Remove missing values in calculation of Mantel correlation. Use this option with care: Permutation tests can be biased, in particular if two matrices had missing values in matching positions. 
parallel 
Number of parallel processes or a predefined socket
cluster. With 
Mantel statistic is simply a correlation between entries of two
dissimilarity matrices (some use cross products, but these are linearly
related). However, the significance cannot be directly assessed,
because there are N(N1)/2 entries for just N observations.
Mantel developed asymptotic test, but here we use permutations of
N rows and columns of dissimilarity matrix. See
permutations
for additional details on permutation tests
in Vegan.
Partial Mantel statistic uses partial correlation
conditioned on the third matrix. Only the first matrix is permuted so
that the correlation structure between second and first matrices is
kept constant. Although mantel.partial
silently accepts other
methods than "pearson"
, partial correlations will probably be
wrong with other methods.
The function uses cor
, which should accept
alternatives pearson
for product moment correlations and
spearman
or kendall
for rank correlations.
The function returns a list of class mantel
with following
components:
Call 
Function call. 
method 
Correlation method used, as returned by

statistic 
The Mantel statistic. 
signif 
Empirical significance level from permutations. 
perm 
A vector of permuted values. The distribution of
permuted values can be inspected with 
permutations 
Number of permutations. 
control 
A list of control values for the permutations
as returned by the function 
Legendre & Legendre (2012, Box 10.4) warn against using partial Mantel correlations.
Jari Oksanen
The test is due to Mantel, of course, but the current implementation is based on Legendre and Legendre.
Legendre, P. and Legendre, L. (2012) Numerical Ecology. 3rd English Edition. Elsevier.
cor
for correlation coefficients,
protest
(“Procrustes test”) for an alternative with
ordination diagrams, anosim
and mrpp
for comparing dissimilarities against
classification. For dissimilarity matrices, see vegdist
or dist
. See bioenv
for selecting
environmental variables.
1 2 3 4 5 6 7 
Loading required package: permute
Loading required package: lattice
This is vegan 2.43
Mantel statistic based on Pearson's productmoment correlation
Call:
mantel(xdis = veg.dist, ydis = env.dist)
Mantel statistic r: 0.3047
Significance: 0.001
Upper quantiles of permutations (null model):
90% 95% 97.5% 99%
0.112 0.144 0.176 0.206
Permutation: free
Number of permutations: 999
Mantel statistic based on Spearman's rank correlation rho
Call:
mantel(xdis = veg.dist, ydis = env.dist, method = "spear")
Mantel statistic r: 0.2838
Significance: 0.001
Upper quantiles of permutations (null model):
90% 95% 97.5% 99%
0.108 0.144 0.166 0.202
Permutation: free
Number of permutations: 999
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