Vegan-Adonis-NMDS-SIMPER
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
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Brandon Gerig
PhD Student
Department of Biological Sciences
University of Notre Dame
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Brandon Gerig
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University of Notre Dame
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Gavin Simpson, PhD