Thank you all very much for the comments! They are so helpful. Yes, I do only have 8 species, and 3 replicates each. It is not ideal, but it's what we have and we have a phylogeny, so I'd like to try some tests incorporating phylogeny.
I probably should have added that I plan on running OLS to test each regression without the tree. This should give me an idea of the general relationship. Regarding Liam's comment in pgls.Ives: Is the "lower=c(1e-8,1e-8)" call of the pgls.Ives call the part where it constrains the slope to (almost)zero? I'll definitely give the MERegPHYSIGv2.m method a try as well, with Tony's diagnostic suggestions. I will also go the LRT route with the data. Thanks very much again for your help! Andrea ~~ Andrea Berardi, PhD Postdoctoral Researcher, Smith Lab EBIO, University of Colorado-Boulder andrea.bera...@colorado.edu On Mar 1, 2015, at 8:42 PM, Liam J. Revell <liam.rev...@umb.edu> wrote: > Hi Andrea. > > This is not presently implemented, but since this is a likelihood method it > would be straightforward to constrain to a slope of zero and then do a LR > test. This would be probably be the easiest way to test a hypothesis about > the regression. > > That being said, as noted in the function documentation, some problems have > been reported with the optimization algorithm for this model, which is simple > and thus may fail to find the ML solution. Consequently, I would encourage > you to look for other implementations of the method so that you can be > confident in your result. I'm not aware of one in R at this time. > > All the best, Liam > > Liam J. Revell, Assistant Professor of Biology > University of Massachusetts Boston > web: http://faculty.umb.edu/liam.revell/ > email: liam.rev...@umb.edu > blog: http://blog.phytools.org > > On 3/1/2015 10:31 PM, Andrea Berardi wrote: >> Hi all, >> >> I'm just learning how to do PGLS analyses, and I'm looking for advice on how >> to evaluate the significance of the regression fit using pgls.Ives in the >> phytools package. I'm using this function because it incorporates sampling >> error of species means, and my data has about 3 individuals per species, >> with 8 species. My goal is to test whether a flower trait predicts the leaf >> trait, while controlling for shared ancestry. Here is the output from >> pgls.Ives: >> >>> fit <- pgls.Ives(Tree, Flower_trait, Leaf_trait) >>> fit >> $beta >> [1] 96.3963098 0.1292656 >> >> $sig2x >> [1] 22218901073 >> >> $sig2y >> [1] 23027587 >> >> $a >> [1] -10063.150 -1204.422 >> >> $logL >> [1] -158.2337 >> >> $convergence >> [1] 0 >> >> $message >> [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH" >> >> I am also running pgls on species averages for the traits using the gls >> function in nlme and the corBrownian and corMartins functions in ape. But, >> we are interested in incorporating the within-species variation in our small >> dataset. >> >> Any suggestions would be welcome! >> >> Thanks for your help, >> Andrea >> >> ~~ >> Andrea Berardi, PhD >> Postdoctoral Researcher, Smith Lab >> EBIO, University of Colorado-Boulder >> >> _______________________________________________ >> R-sig-phylo mailing list - R-sig-phylo@r-project.org >> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo >> Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/ >> _______________________________________________ R-sig-phylo mailing list - R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
