Vegan-Adonis-NMDS-SIMPER
You mean `betadisper()`? This simply computes a multivariate dispersion about the kth group centroid for k groups. If you can express the "levels within main effects" as a factor variable defining the groups then `betadisper()` could work with that, but I'm not quite following what you want to do. `adonis()` will test whether the groups means (defined by the combinations of the levels of the covariate factors) differ. `betadisper()` can test if there are different "variances" for the same groups. If there are different variances, one might question the results from `adonis()` if it indicated that the observed group means was inconsistent with the hypothesis of equal group means. This inconsistency may be due solely or in part to the heterogeneity of dispersions (variances). Is that what you want to test/investigate? G
On 26 March 2014 09:57, 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",permutations=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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