[R-sig-phylo] Phylogenetic ANOVA or PGLS for categorical data?
Hello everyone, I am comparing a categorical data vs. a continues data, but the continues data is a frequency of an observed parameter. I'm considering using phylogenetic ANOVA (Garland 1993) or PGLS for categorical data. But, I am not sure with one is more appropriate to my data. I would like to ask if someone have any advice about the subject, or can recommend me a paper that compare these analyses. All the best - Carlos Bagolini-Jr -- Carlos Biagolini-Jr. Bacharel em Ci�ncias Biol�gicas - Universidade Federal de Lavras Mestrando em Diversidade Biol�gica e Conserva��o - Universidade Federal de S�o Carlos http://lattes.cnpq.br/4086237188108947 [[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] Phylogenetic ANOVA with multiple levels
Hi all I am trying to analyze the integration between organs in root systems of angisoperms. My idea is testing if three different angiosperm groups integrate vascular tissue across root orders in the same way. So far I have been working with linear mixed effect models to test the idea, like in this example, nesting the species within the clades I am studying in a nested model: model-lmer(log(Stele)~log(RootDiameter)+Root.Order*Clade+Site+(1|Clade/Species),data=dataRoot) I am wondering if it is possible to integrate the phylogeny in a more straight-forward way. I check options in phytools and gieger, but in both cases the phylogenetic anova seem to test only one categorical variable at the time and require same number of tips in the tree and the dataset. In my case, even if I use species means I will have three times the number of tips, since I have three orders of roots to integrate. I'll appreciate any hints about how to solve this. Thanks in advance. -- Oscar Valverde PhD candidate Department of Biological Sciences Kent State University [[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] Phylogenetic ANOVA
Hello, Some colleagues and I are running some phylogenetic ANOVAS using the geiger package. In some of the analyses we get the same phylogentic p-value (very small p-value) even though the F-statistic differs between the two analyses, albeit it being relatively high in both instances. We were wondering why this arises, to get better grip on how the analysis works. We thought it may have to do with the randomizations to calculate the phylogenetic p-value. Or that the F-statistics are quite high... Below are two examples : m11-phy.anova(tree1,tmax,biozone,data.names=X,nsim=1000) Standard ANOVA: Analysis of Variance Table Response: td$data Df Sum Sq Mean Sq F valuePr(F) group 1 967.96 967.96 155.88 3.057e-12 *** Residuals 25 155.246.21 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Phylogenetic p-value: 0.000999001 m12-phy.anova(tree1,wt,biozone,data.names=X,nsim=1000) Standard ANOVA: Analysis of Variance Table Response: td$data Df Sum Sq Mean Sq F valuePr(F) group 1 602.88 602.88 109.01 1.333e-10 *** Residuals 25 138.265.53 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Phylogenetic p-value: 0.000999001 Cheers, Alejandro __ Alejandro Gonzalez Voyer Post-doc NEW ADDRESS NEW E-MAIL Estación Biológica de Doñana (CSIC) Avenida Américo Vespucio s/n 41092 Sevilla Spain E-mail: alejandro.gonza...@ebd.csic.es Tel: +34- 954 466700, ext 1749 Website (From my previous position): http://www.iee.uu.se/zooekol/default.php?type=personalpagelang=enid=146 [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Re: [R-sig-phylo] Phylogenetic ANOVA
Just to clarify the point - the null distribution for the test-statistic (F) in this method is generated by Brownian motion simulation on the phylogeny. The P-value of the ANOVA is thus obtained by comparing the observed test-statistic to simulated test-statistics (for an arbitrarily large number of simulations). The reference to this is: Garland, T. Jr., A. W. Dickerman, C. M. Janis, J. A. Jones. 1993. Phylogenetic analysis of covariance by computer simulation. Syst. Biol. 42: 265-292. (http://www.jstor.org/stable/2992464) Thus, if you have a test-statistic (F) more extreme then that obtained for every last one of your simulated datasets, then the P-value will be entirely determined by the number of simulations that are used (as Luke says). This seems to be case for your data (not surprising given the very large values for F that were obtained). - Liam Liam J. Revell NESCent, Duke University web: http://anolis.oeb.harvard.edu/~liam/ NEW email: lrev...@nescent.org Luke Harmon wrote: Yes that's a direct result of the number of simulations - if all of the simulated F statistics are smaller than the test statistics, then you will get: p = 1/(n+1) where n is the number of simulated data sets. lh On Jul 26, 2010, at 8:44 AM, Alejandro Gonzalez V wrote: Hello, Some colleagues and I are running some phylogenetic ANOVAS using the geiger package. In some of the analyses we get the same phylogentic p-value (very small p-value) even though the F-statistic differs between the two analyses, albeit it being relatively high in both instances. We were wondering why this arises, to get better grip on how the analysis works. We thought it may have to do with the randomizations to calculate the phylogenetic p-value. Or that the F-statistics are quite high... Below are two examples : m11-phy.anova(tree1,tmax,biozone,data.names=X,nsim=1000) Standard ANOVA: Analysis of Variance Table Response: td$data Df Sum Sq Mean Sq F valuePr(F) group 1 967.96 967.96 155.88 3.057e-12 *** Residuals 25 155.246.21 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Phylogenetic p-value: 0.000999001 m12-phy.anova(tree1,wt,biozone,data.names=X,nsim=1000) Standard ANOVA: Analysis of Variance Table Response: td$data Df Sum Sq Mean Sq F valuePr(F) group 1 602.88 602.88 109.01 1.333e-10 *** Residuals 25 138.265.53 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Phylogenetic p-value: 0.000999001 Cheers, Alejandro __ Alejandro Gonzalez Voyer Post-doc NEW ADDRESS NEW E-MAIL Estación Biológica de Doñana (CSIC) Avenida Américo Vespucio s/n 41092 Sevilla Spain E-mail: alejandro.gonza...@ebd.csic.es Tel: +34- 954 466700, ext 1749 Website (From my previous position): http://www.iee.uu.se/zooekol/default.php?type=personalpagelang=enid=146 [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Luke Harmon Assistant Professor Biological Sciences University of Idaho 208-885-0346 lu...@uidaho.edu ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
