You might also want to read about the background, starting with these two papers, both available at my website:
Ives, A. R., and T. Garland, Jr. 2010. Phylogenetic logistic regression for binary dependent variables. Systematic Biology 59:9-26. Ives, A. R., and T. Garland, Jr. 2014. Phylogenetic regression for binary dependent variables. Pages 231-261 in Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology: Concepts and Practice, L. Z. Garamszegi, ed. Springer: Heidelberg. Cheers, Ted Theodore Garland, Jr., Professor Department of Biology University of California, Riverside Riverside, CA 92521 Office Phone: (951) 827-3524 Facsimile: (951) 827-4286 (not confidential) Email: tgarl...@ucr.edu http://www.biology.ucr.edu/people/faculty/Garland.html http://scholar.google.com/citations?hl=en&user=iSSbrhwAAAAJ Director, UCR Institute for the Development of Educational Applications Editor in Chief, Physiological and Biochemical Zoology Fail Lab: Episode One http://testtube.com/faillab/zoochosis-episode-one-evolution http://www.youtube.com/watch?v=c0msBWyTzU0 ________________________________________ From: R-sig-phylo [r-sig-phylo-boun...@r-project.org] on behalf of Florian Boucher [floflobouc...@gmail.com] Sent: Tuesday, January 26, 2016 8:34 AM To: Knappová Jana Cc: r-sig-phylo@r-project.org Subject: Re: [R-sig-phylo] multiple regression with binomial distribution Hi Jana, If your data are proportions, you might want to model their logit, ie log(X/(1-X)), rather than their raw value. You can then use PGLS in the same manner as you did. An ML value of 0 for lambda indicates that you are actually fitting a non-phylogenetic model, but it is safer to allow for lambda to vary in case there would be signal in the residuals of the regression. If your data are 0/1, then you should rather use phylogenetic logistic regression. This is implemented for example in the 'phyloglm' function in the R package 'phylolm'. Cheers, Florian 2016-01-26 16:16 GMT+01:00 Knappová Jana <jana.knapp...@ibot.cas.cz>: > Hi everyone, > > I am not very familiar with phylogenetics, but i would like to incorporate > it somehow into my work and i appreciate any suggestions. > > Is it possible to use any kind of phylogenetically informed analysis in > case of multiple regression (one response ~ multiple predictors) in case I > assume binomial distribution of response variable? I try to explain species > occurrence (proportional data) by a couple of species traits. > > I tried pgls function from "caper" R package, but I am not sure about it. > Generally, it seems that there is not strong signal in my data, when I used > lambda="ML" than lambda was set to zero. > > Thanks > > Jana Knappová > Botanický ústav AV ČR, v. v. i. | Institute of Botany of the CAS > Zámek 1, 252 43 Průhonice | Zamek 1, CZ-25243 Pruhonice > Česká republika | Czech Republic > jana.knapp...@ibot.cas.cz > www.ibot.cas.cz > www.pruhonickypark.cz > Telefon: 271015401, 737375227 | Phone: +420-271015401, 737375227 > Fax: 271015105 | Fax: +420-271015105 > _______________________________________________ > 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/ -- Florian Boucher Postdoctoral researcher, Institute of Systematic Botany, Zürich [[alternative HTML version deleted]] _______________________________________________ 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/
