Hi Alberto, OK, I think the bigger and more general issue is how to "correct" for correlations with body size. this is an issue in many circumstances, both biologically and statistically, aside from any questions about how best to test for or quantify phylogenetic signal. I think that if you get it right from the biological/statistical perspective then you will also have the answer regarding what to do for phylogenetic signal.
When you compute a ratio (divide by a measure of body size) in hopes of "removing" the effects of body size you are implicitly assuming that the trait varies directly with the measure of body size. For example, computing tail length/body length for snakes might be a good way to "remove" the effects of body size if snakes of all sizes, on average, have tails of the same relative length. However, many traits do not vary directly with any measure of body size. For example, resting metabolic rate generally does not vary directly with body mass. Rather, it scales on body mass (log-log plot) with a slope of about 0.6-0.8. Hence, if you compute the ratio metabolic rate/body mass it will show a negative relation with body mass, and so you have not "removed" the correlation with body mass. In such a case, it is generally better to do the log-log regression and compute residuals. Or, you can do what I described previously (see Blomberg et al., 2003, pages 720-721). In some cases, you might have strong a priori knowledge or particular biological needs that would lead you to trust computing a ratio for your particular purposes. For example, one might compute the ratio of forelimb length divided by hindlimb length of lizards for some purposes. In general, however, the regression approach is probably safest if you want to then analyze a trait that is no longer correlated with body size. Cheers, Ted ---- Original message ---- Date: Wed, 23 Mar 2011 02:13:36 +0200 From: Alberto Gallano <alberto....@gmail.com> Subject: Re: [R-sig-phylo] How to detect phylogenetic signal (lambda) in one unscaled trait? To: Alejandro Gonzalez <alejandro.gonza...@ebd.csic.es> Cc: R-phylo Mailing-list <r-sig-phylo@r-project.org> >Thanks Alejandro, > >yes, I see this difference. I think my question is: if the goal is to assess >phylogenetic signal in a trait, after accounting for interspecific >differences in body size, which of these two alternatives is preferable? >They both seem to calculate lambda after correcting for body size. Is one >way more correct, given the above stated goal? > >regards, > >Alberto > > > >On Wed, Mar 23, 2011 at 1:53 AM, Alejandro Gonzalez < >alejandro.gonza...@ebd.csic.es> wrote: > >> Hi Alberto, >> >> The results differ between the two approaches because you're actually >> estimating two different things. >> >> gls(logY ~ logX, correlation=corPagel(1, tree), method="ML") >> >> >> Will give you the estimate of lambda for the residuals of the fitted model. >> >> while: >> >> fitContinuous(tree, log(Y/X), model="lambda") >> >> >> will give you the lambda value of the ratio of the two traits. >> >> >> Cheers, >> >> Alejandro >> >> On 23, Mar 2011, at 12:47 AM, Alberto Gallano wrote: >> >> Thanks Ted and Joe, that helps a lot with my understanding. >> >> >> Given then that the variables should be on a log scale, as you suggest, is >> there any reason to chose a regression model estimate of lambda: >> >> gls(logY ~ logX, correlation=corPagel(1, tree), method="ML") >> >> where X is a body size proxy (i.e., scaling is done in the model), over a >> ratio approach?: >> >> fitContinuous(tree, log(Y/X), model="lambda") >> >> These seem to produce different results. Is there a preference for one >> other >> the other in a comparative methods context? Or is this just a question of >> whether one prefers to size 'correct' using ratios vs residuals? >> >> kind regards, >> >> Alberto >> >> >> On Wed, Mar 23, 2011 at 1:30 AM, Joe Felsenstein <j...@gs.washington.edu >> >wrote: >> >> >> Ted wrote: >> >> >> Following on that, various papers (I can't remember the references) >> >> have argued that imagining Brownian-like evolution of body size on a >> >> log scale seems reasonable. That is, it should be equally easy for an >> >> elephant's body size to evolve 10% as for a mouse's body size to >> >> evolve 10%, and to analyze that you want everybody on a log scale. >> >> Extending this, you would want to use log(Y/X) or log(Y/[X raised to >> >> some allometric slope]). >> >> >> It's just easier to put all variables onto their log scales, so you >> >> have log(X), log(Y), log(Z) and then the allometric stuff just >> >> corresponds to linear combinations there, which you already have >> >> machinery to do. >> >> >> The recommendation to use log scales is a very old one: I talk >> >> about it in my "Theoretical Evolutionary Genetics" free e-text. >> >> But is older than that. Falconer has a whole chapter on "Scale" >> >> in his 1960 "Introduction of Quantitative Genetics". Sewall >> >> Wright has a discussion of it in Chapter 10 of his 1968 first >> >> volume of "Evolution and the Genetics of Populations" (see pages >> >> 227ff.). But it is older than those -- for Wright also says (p. 228): >> >> "Galton, as long ago as 1879, noted that the logarithms of measurements >> >> of organisms may be more appropriate than the measurements >> >> themselves on the hypothesis that growth factors tend to contribute >> >> constant percentage increments rather than constant absolute ones." >> >> The old biometrical types of the 1930s and 1940s knew all about >> >> this (though taking logarithms was tedious). It is only the more >> >> recent researchers who don't know it. >> >> >> Joe >> >> ---- >> >> Joe Felsenstein j...@gs.washington.edu >> >> Department of Genome Sciences and Department of Biology, >> >> University of Washington, Box 355065, Seattle, WA 98195-5065 USA >> >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> R-sig-phylo mailing list >> R-sig-phylo@r-project.org >> https://stat.ethz.ch/mailman/listinfo/r-sig-phylo >> >> >> __________________________________ >> >> Alejandro Gonzalez Voyer >> >> Post-doc >> >> NEW ADDRESS >> >> Estaci�n Biol�gica de Do�ana >> Consejo Superior de Investigaciones Cient�ficas (CSIC) >> Av Am�rico Vespucio s/n >> 41092 Sevilla >> Spain >> >> Tel: + 34 - 954 466700, ext 1749 >> >> E-mail: alejandro.gonza...@ebd.csic.es >> >> *Web page*: https://docs.google.com/View?id=dfs328dh_14gwwqsxcg >> >> >> >> > > [[alternative HTML version deleted]] > >________________ >_______________________________________________ >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
