| anosim {vegan} | R Documentation |
Analysis of similarities (ANOSIM) provides a way to test statistically whether there is a significant difference between two or more groups of sampling units.
anosim(dis, grouping, permutations=1000, strata)
dis |
Dissimilarity matrix. |
grouping |
Factor for grouping observations. |
permutations |
Number of permutation to assess the significance of the ANOSIM statistic. |
strata |
An integer vector or factor specifying the strata for permutation. If supplied, observations are permuted only within the specified strata. |
Analysis of similarities (ANOSIM) provides a way to test statistically
whether there is a significant difference between two or more groups
of sampling units. Function anosim operates directly on a
dissimilarity matrix. A suitable dissimilarity matrix is produced by
functions dist or vegdist. The
method is philosophically allied with NMDS ordination
(isoMDS), in that it uses only the rank order of
dissimilarity values.
If two groups of sampling units are really different in their species
composition, then compositional dissimilarities between the groups
ought to be greater than those within the groups. The anosim
statistic R is based on the difference of mean ranks between
groups (r_B) and within groups (r_W):
R = (r_B - r_W)/(N (N-1) / 4)
The divisor is chosen so that R will be in the interval -1 ... +1, value 0 indicating completely random grouping.
The statistical significance of observed R is assessed by permuting the grouping vector to obtain the empirical distribution of R under null-model.
The function has summary and plot methods. These both
show valuable information to assess the validity of the method: The
function assumes that all ranked dissimilarities within groups
have about equal median and range. The plot method uses
boxplot with options notch=TRUE and
varwidth=TRUE.
The function returs a list of class anosim with following items:
call |
Function call. |
statistic |
The value of ANOSIM statistic R |
signif |
Significance from permutation. |
perm |
Permutation values of R |
class.vec |
Factor with value Between for dissimilarities
between classes and class name for corresponding dissimilarity
within class. |
dis.rank |
Rank of dissimilarity entry. |
dissimilarity |
The name of the dissimilarity index: the
"method" entry of the dist object. |
I don't quite trust this method. Somebody should study its
performance carefully. The function returns a lot of information
to ease further scrutiny. Most anosim models could be analysed
with adonis which seems to be a more robust alternative.
Jari Oksanen, with a help from Peter R. Minchin.
Clarke, K. R. (1993). Non-parametric multivariate analysis of changes in community structure. Australian Journal of Ecology 18, 117-143.
mrpp for a similar function using original
dissimilarities instead of their ranks.
dist and vegdist for obtaining
dissimilarities, and rank for ranking real values. For
comparing dissimilarities against continuous variables, see
mantel. Function adonis is a more robust
alternative that should preferred.
data(dune) data(dune.env) dune.dist <- vegdist(dune) attach(dune.env) dune.ano <- anosim(dune.dist, Management) summary(dune.ano) plot(dune.ano)