On Wed, 2009-12-09 at 10:25 +0100, gabriel singer wrote: > Gian, > > You may also want to use betadisper() to check whether the host effect > is due to differences in "location" or "dispersion" (or both). This is > equivalent to checking homogeneity of variance when running a classical > ANOVA. > > cheers, g
Good point Gabriel, but I'd caution against using betadisper just at the moment in Vegan. A user, and subsequently confirmed by Jari, notified us that the default (and currently only) method using the dispersion around the group centroid (average) and a permutation test was anti-conservative. Since then Jari has written code to allow us to include the dispersion around the spatial median within betadisper and initial tests suggests this has the right Type I error rate in the permutation test. I had hoped to have included this by now, but having been under the weather for the past month I have not yet finished working on it. An updated version should be on r-forge in the next few days. G > > > Gian Maria Niccolò Benucci wrote: > > Jari, Gavin, Chris, Gabriel and Carsten... > > > > Many thank you all for your support and kindness... and for your competence > > and experience that could not be ever comparized to mine at least in that > > stuffs... > > > > Gabriel said: .*..I found this mailing list very helpful many times for my > > own questions, but also very informative when just following the threads on > > other questions... > > * > > I complitely agree about that, so here I am to go deeper inside my > > statistical problems... > > > > As Gavin argued the plot: > > > > > >> NMS.2$stress > >> > > [1] 24.53723 > > > >> NMS.3$stress > >> > > [1] 16.29226 > > > >> NMS.4$stress > >> > > [1] 11.79951 > > > >> plot(2:4, c(24.53723, 16.29226, 11.79951), type = "b") > >> > > > > didn't show significally differences... > > > > ...so as him suggested I did the stressplot() and got shepard graphs... > > (just to specify, sqrtABCD is the square roots transforming of the species > > matrix) > > > > > >> stressplot(NMS.2) > >> > > Using step-across dissimilarities: > > Too long or NA distances: 230 out of 780 (29.5%) > > Stepping across 780 dissimilarities... > > > > > > Non-metric fit, R2=0.94 > > Linear fit, R2=0.719 > > > > > >> stressplot(NMS.3) > >> > > Using step-across dissimilarities: > > Too long or NA distances: 230 out of 780 (29.5%) > > Stepping across 780 dissimilarities... > > > > > > Non-metric fit, R2=0.973 > > Linear fit, R2=0.815 > > > > > >> stressplot(NMS.4) > >> > > Using step-across dissimilarities: > > Too long or NA distances: 230 out of 780 (29.5%) > > Stepping across 780 dissimilarities... > > > > Non-metric fit, R2=0.986 > > Linear fit, R2=0.875 > > > > >From this data is clear that the fit is better for the NMS.4 (k=4) also the > > blue points into the graph are more near to red line, less spare around the > > graph space... > > > > But maybe the R2 values of the NMS.2 aren't so bad in correlation terms, are > > they? > > > > In reason of what Gabriel said: *...I personally like a combination of NMDS > > with the permutational MANOVA approach (by Marti Anderson) implemented in > > the function adonis() in vegan. You can use the same dissimilarity measure > > (Bray-Curtis) used for the NMDS and can test the "Area" vs. the "Host" > > effect on parasite (was it?) composition. I think that could be a very > > useful complement to an NMDS-derived ordination plot and then you may also > > regard high-stress "representations" (and that´s what all the > > low-dimensional ordination plots really ARE!) in a different light.*.. > > > > > > > >> adonis(sqrtABCD ~ Host*Community, method="bray", data=env.table, > >> > > permutations=99) > > > > Call: > > adonis(formula = sqrtABCD ~ Host * Community, data = env.table, > > permutations = 99, method = "bray") > > > > Df SumsOfSqs MeanSqs F.Model R2 Pr(>F) > > Host 1.00000 1.64429 1.64429 5.47874 0.1242 0.01 ** > > Community 2.00000 0.78834 0.39417 1.31337 0.0596 0.23 > > Residuals 36.00000 10.80441 0.30012 0.8162 > > Total 39.00000 13.23705 1.0000 > > --- > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > > > > > ...So, I would explain a little about my datasets: > > > > - the species matrix is done by roots samples in which were counted the > > ectomycorrhizal fungal species present (cells entities are different tips > > individuals); > > - sample where taken into four "Area" (A,B,C,D). The ares are about 30 > > meters far away one to each other; > > - areas A and B are both form Corylus roots while areas C and D are both > > from Ostrya roots. > > > > To be more clear that is the enviromental matix used: > > > > > >> env.table > >> > > Community Host > > A1 A Corylus > > A2 A Corylus > > A3 A Corylus > > A4 A Corylus > > A5 A Corylus > > A6 A Corylus > > A7 A Corylus > > A8 A Corylus > > A9 A Corylus > > A10 A Corylus > > B1 B Corylus > > B2 B Corylus > > B3 B Corylus > > B4 B Corylus > > B5 B Corylus > > B6 B Corylus > > B7 B Corylus > > B8 B Corylus > > B9 B Corylus > > B10 B Corylus > > C1 C Ostrya > > C2 C Ostrya > > C3 C Ostrya > > C4 C Ostrya > > C5 C Ostrya > > C6 C Ostrya > > C7 C Ostrya > > C8 C Ostrya > > C9 C Ostrya > > C10 C Ostrya > > D1 D Ostrya > > D2 D Ostrya > > D3 D Ostrya > > D4 D Ostrya > > D5 D Ostrya > > D6 D Ostrya > > D7 D Ostrya > > D8 D Ostrya > > D9 D Ostrya > > D10 D Ostrya > > > > > > ...maybe could be helpfull to say that I calculated diversity indices > > (richness, shannon, simpson and evenness) for my 4 areas and I use ANOVA to > > see if them are diffent one from each other. > > The results show me that area A and B are always different form areas C and > > D but no differences are between them, so clearly Corylus fungal community > > is alwasy different from Ostrya one. > > > > ...So, I think that "Host" effect is clear while the effect of "Community" > > couldn't be the same in reason to that areas are similar 2 by 2, ...is it > > right? > > > > When I plot the MNS.2 and I watch to the Graph I clearly see that sample > > points of A,B areas or Corylus are positioned on the left side while areas C > > and D of Ostrya are more sparse and are positioned into the low right > > side... > > > > So, what else to say... I'll leave you space for any comments :)))) > > > > Tank you all, > > > > Gian > > > > [[alternative HTML version deleted]] > > > > > > ------------------------------------------------------------------------ > > > > _______________________________________________ > > R-sig-ecology mailing list > > R-sig-ecology@r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > > > -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology