[R-sig-eco] Vegan-Adonis-NMDS-SIMPER

Fri Mar 28 16:42:16 CET 2014

Hi Steve,

I agree with your points here; I simply wanted to avoid the impression
that `betadisper()` did anything with the centroids. It did seem like
the OP and some others had got this impression.

I also agree that the PCoA way of computing the centroids is a useful
tool not just for `betadisper()`; there is no reason that this be
restricted to running a `betadisper()` just to get that information.
I'll see about removing this functionality from being embedded only
`betadisper()` and abstract it out to a user-visible function that
`betadisper()` can use internally.

G

On 27 March 2014 12:28, Steve Brewer <jbrewer at olemiss.edu> wrote:
> Gavin and Brandon,
>
> Yes, I am aware that betadisper() does not actually give you a test of
> differences between centroids, but the fact that it does calculate
> centroids is quite valuable for interpretation, in my opinion, especially
> when using non-euclidean distance matrices (e.g., Bray-Curtis) and also if
> you would prefer NOT to do additional pairwise tests between levels, but
> still would like to have some idea as to which pairwise differences
> between levels might be most responsible for the effect. When using
> bray-curtis distances, you can't get centroids by calculating averages of
> abundances among the observations of interest. If you just want to use a
> NMDS ordination with levels symbol-coded to make them distinct, that's
> fine. Sometimes folks calculate the average axis score per group or level
> of group and plot that. That's fine, too. The nice thing about obtaining
> centroids calculated using betadisper() is that they are based on a
> principal coordinates analysis that uses ALL the axes, not just the first
> two or three axes in the ordination. It is likely that if the first two or
> three axes of the NMDS explain most of the important variation, the
> average scores per level for those three axes will probably tell the same
> information as the centroids will.
>
> Even though it wasn't intended for this purpose, Sharon Graham and I,
> together, figured out that you could use the centroids calculated by
> betadisper() to analyze split-plot and repeated-measures designs using
> adonis. So, its value extends beyond what it was intended for.
>
>
> Steve
>
> J. Stephen Brewer
> Professor
> Department of Biology
> PO Box 1848
>  University of Mississippi
> University, Mississippi 38677-1848
>  Brewer web page - http://home.olemiss.edu/~jbrewer/
> FAX - 662-915-5144
> Phone - 662-915-1077
>
>
>
>
> On 3/27/14 10:47 AM, "Gavin Simpson" <ucfagls at gmail.com> wrote:
>
>>Note that `betadisper()` only considers statistically dispersions
>>about the group centroids. It might show the centroids and return
>>their values, but it doesn't consider differences in those centroids.
>>As far is `betadisper()` is concerned, the group centroids could all
>>be made exactly equal and it wouldn't change the results as it is only
>>the spread about the centroid that is used.
>>
>>HTH
>>
>>G
>>
>>On 27 March 2014 06:47, Brandon Gerig <bgerig at nd.edu> wrote:
>>> Hi Steve,
>>>
>>> Yes, this is precisely what I am interested in doing. It seems like
>>> betadisper might be a good way to visualize differences/similarities in
>>>the
>>> dispersion and examine differences among centroids for the levels
>>>within a
>>> factor. Am I correct in thinking that if I conduct additional PERMANOVA
>>> tests on a reduced data set, I could be evaluating differences between
>>>the
>>> levels of a main effect?
>>>
>>> Could anyone provide a citation for a paper that uses a similar
>>>procedure?
>>>
>>>
>>> On Wed, Mar 26, 2014 at 3:21 PM, Steve Brewer <jbrewer at olemiss.edu>
>>>wrote:
>>>
>>>> Brandon,
>>>>
>>>> Are you asking if you can use betadisper as a substitute for post-anova
>>>> pairwise comparisons among levels? After using betadisper to obtain
>>>> dispersions, I believe you can plot the centroids for each level. In
>>>> addition to telling you if the dispersions differ among levels, you
>>>>could
>>>> see how the centroids differ from one another. Is this what you want to
>>>> know? If so, realize that it won't give you pairwise significance tests
>>>> for differences between levels. For that, you might want to do
>>>>additional
>>>> permanovas on reduced datasets containing only the two levels you want
>>>>to
>>>> compare. You could then adjust the p-values for multiple tests after
>>>>the
>>>> fact.
>>>>
>>>> Hope this helps,
>>>>
>>>> Steve
>>>>
>>>>
>>>> J. Stephen Brewer
>>>> Professor
>>>> Department of Biology
>>>> PO Box 1848
>>>>  University of Mississippi
>>>> University, Mississippi 38677-1848
>>>>  Brewer web page - http://home.olemiss.edu/~jbrewer/
>>>> FAX - 662-915-5144
>>>> Phone - 662-915-1077
>>>>
>>>>
>>>>
>>>>
>>>> On 3/26/14 10:57 AM, "Brandon Gerig" <bgerig at nd.edu> wrote:
>>>>
>>>> >Thanks for the words of caution on simper.
>>>> >
>>>> >Am I completely off base in thinking that betadiver function
>>>>(analgous to
>>>> >Levene's test) could be used to examine variation between levels
>>>>within
>>>> >main effects?
>>>> >
>>>> >Cheers
>>>> >
>>>> >
>>>> >On Mon, Mar 24, 2014 at 5:08 PM, Brandon Gerig <bgerig at nd.edu> wrote:
>>>> >
>>>> >> I am assessing the level of similarity between PCB congener
>>>>profiles in
>>>> >> spawning salmon and resident stream in stream reaches with and
>>>>without
>>>> >> salmon to determine if salmon are a significant vector for PCBs in
>>>> >> tributary foodwebs of the Great Lakes.
>>>> >>
>>>> >> My data set is arranged in a matrix where the columns represent the
>>>> >> congener of interest and the rows represent either a salmon
>>>>(migratory)
>>>> >>or
>>>> >> resident fish (non migratory) from different sites.  You can think
>>>>of
>>>> >>this
>>>> >> in a manner analogous to columns representing species composition
>>>>and
>>>> >>rows
>>>> >> representing site.
>>>> >>
>>>> >> Currently, I am using the function Adonis to test for dissimilarity
>>>> >> between fish species, stream reaches (with and without salmon) and
>>>>lake
>>>> >> basin (Superior, Huron, Michigan).
>>>> >> The model statement is:
>>>> >>
>>>> >>
>>>>
>>>>>>m1<adonis(congener~FISH*REACH*BASIN,data=pcbcov,method="bray",permutat
>>>>>>ion
>>>> >>s=999)
>>>> >>
>>>> >> The output indicates significant main effects of FISH, REACH, and
>>>>BASIN
>>>> >> and significant interactions between FISH and BASIN, and BASIN and
>>>> >>REACH.
>>>> >>
>>>> >> Is it best to then interpret this output via an NMDS ordination
>>>>plot or
>>>> >> use something like the betadiver function to examine variances
>>>>between
>>>> >>main
>>>> >> effect levels or both?
>>>> >>
>>>> >> Also,  can anyone recommend a procedure to identify the congeners
>>>>that
>>>> >> contribute most to the dissimilarity between fish, reaches, and
>>>> >>basins?. I
>>>> >> was thinking the SIMPER procedure but am not yet sold.
>>>> >>
>>>> >> Any advice is appreciated!
>>>> >> --
>>>> >> Brandon Gerig
>>>> >> PhD Student
>>>> >> Department of Biological Sciences
>>>> >> University of Notre Dame
>>>> >>
>>>> >
>>>> >
>>>> >
>>>> >--
>>>> >Brandon Gerig
>>>> >PhD Student
>>>> >Department of Biological Sciences
>>>> >University of Notre Dame
>>>> >
>>>> >       [[alternative HTML version deleted]]
>>>> >
>>>> >_______________________________________________
>>>> >R-sig-ecology mailing list
>>>> >R-sig-ecology at r-project.org
>>>> >https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>> Brandon Gerig
>>> PhD Student
>>> Department of Biological Sciences
>>> University of Notre Dame
>>>
>>>         [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
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>>
>>
>>
>>--
>>Gavin Simpson, PhD
>
>

-- 
Gavin Simpson, PhD