permutest.betadisper {vegan} | R Documentation |

Implements a permutation-based test of multivariate homogeneity of
group dispersions (variances) for the results of a call to
`betadisper`

.

## S3 method for class 'betadisper': permutest(x, pairwise = FALSE, control = permControl(nperm = 999), ...)

`x` |
an object of class `"betadisper"` , the result of a
call to `betadisper` . |

`pairwise` |
logical; perform pairwise comparisons of group means? |

`control` |
a list of control values for the permutations
to replace the default values returned by the function
`permControl` |

`...` |
Arguments passed to other methods. |

To test if one or more groups is more variable than the others, ANOVA
of the distances to group centroids can be performed and parametric
theory used to interpret the significance of F. An alternative is to
use a permutation test. `permutest.betadisper`

permutes model
residuals to generate a permutation distribution of F under the Null
hypothesis of no difference in dispersion between groups.

Pairwise comparisons of group mean dispersions can be performed by
setting argument `pairwise`

to `TRUE`

. A classical t test
is performed on the pairwise group dispersions. This is combined with a
permutation test based on the t statistic calculated on pairwise group
dispersions. An alternative to the classical comparison of group
dispersions, is to calculate Tukey's Honest Significant Differences
between groups, via `TukeyHSD.betadisper`

.

`permutest.betadisper`

returns a list of class
`"permutest.betadisper"`

with the following components:

`tab` |
the ANOVA table which is an object inheriting from class
`"data.frame"` . |

`pairwise` |
a list with components `observed` and
`permuted` containing the observed and permuted p-values for
pairwise comparisons of group mean distances (dispersions or variances). |

`groups` |
character; the levels of the grouping factor. |

`control` |
a list, the result of a call to
`permControl` . |

Gavin L. Simpson

Anderson, M.J. (2006) Distance-based tests for homogeneity of
multivariate dispersions. *Biometrics* **62(1)**, 245–253.

Anderson, M.J., Ellingsen, K.E. & McArdle, B.H. (2006) Multivariate
dispersion as a measure of beta diversity. *Ecology Letters*
**9(6)**, 683–693.

For the main fitting function see `betadisper`

. For
an alternative approach to determining which groups are more variable,
see `TukeyHSD.betadisper`

.

data(varespec) ## Bray-Curtis distances between samples dis <- vegdist(varespec) ## First 16 sites grazed, remaining 8 sites ungrazed groups <- factor(c(rep(1,16), rep(2,8)), labels = c("grazed","ungrazed")) ## Calculate multivariate dispersions mod <- betadisper(dis, groups) mod ## Perform test anova(mod) ## Permutation test for F permutest(mod, pairwise = TRUE) ## Tukey's Honest Significant Differences (mod.HSD <- TukeyHSD(mod)) plot(mod.HSD)

[Package *vegan* version 1.16-32 Index]