On 27.3.2014, at 17.54, "Gavin Simpson" <ucfagls at gmail.com> wrote:
No, that will just consider the dispersions *about the centroids* not
location shifts of the centroids. The latter is what `adonis()` does,
but we don't have pairwise comparisons (with/without permutation test)
there or the Tukey post-hoc tests. I suppose we *could* automate the
process that Steve suggests, just as I automated it for
`betadisper()`, and I think this has been raised before, but it hasn't
risen to the top of anyone's TODO list yet to actually see it
implemented. Patches welcome :-) !
G
On 27 March 2014 06:55, Johannes Bj?rk <bjork.johannes at gmail.com> wrote:
Hi,
For that I believe you can run TukeyHSD.betadisper... to getting significant values between levels. see ?TukeyHSD.betadisper
Cheers,
On Mar 27, 2014, at 1:47 PM, Brandon Gerig 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",permutation
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
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