Hi Gopal,
If your data are really zero-inflated, then my impression has been the best thing to do with this situation is to break up your dependent data points to test two hypotheses: 1 a logistic model for what determines whether the outcome is a zero or >0, 2 a linear or other appropriate model for what determines the continuous value of non-zero outcomes. That's been my impression at least that with zero inflation there is no longer any single test or distribution that is very applicable. There are some approaches that do all this in a single model, but when you look under the hood it still is breaking the data into two parts with two models http://stats.idre.ucla.edu/r/dae/zip/ To make this phylogenetic, I think you want to run the appropriate phylogenetic code for the logistic outcome with the 0/1 coding of the variable, and then pgls for the continuous value of all the >0 outcomes. MCMCglmm could do this, but also there is a phylogenetic logistic regression that Ives and Garland (2010) produced with Matlab code. I'm not sure if that routine was ever moved into R code. Maybe someone else on this list knows? For the pgls, you could use MCMCglmm, ape, or caper. Here's the Ives and Garland ref: Ives, A.R., & Garland, T. (2010). Phylogenetic logistic regression for binary dependent variables. Systematic Biology, 59, 9_26. This is all assuming the data really are zero-inflated, which I wouldn't consider as quite the same as right-skewed. A zero-inflated distribution after the arcsine transform would have a big spike of zeros and then with a normal-ish looking distribution of positive values. Best Luke Luke J Matthews Behavioral and Social Scientist RAND Corporation Message: 1 Date: Wed, 15 Mar 2017 11:51:21 +0000 From: Manabu Sakamoto <manabu.sakam...@gmail.com<mailto:manabu.sakam...@gmail.com>> To: Gopal Murali <goopaalmur...@gmail.com<mailto:goopaalmur...@gmail.com>> Cc: R phylo mailing list mailing list <r-sig-phylo@r-project.org<mailto:r-sig-phylo@r-project.org>> Subject: Re: [R-sig-phylo] Zero inflated model accounting for phylogeny Message-ID: <caerhmt3chufva2ek_aidprwktjvk5qelhuzkyrvvxknzjdo...@mail.gmail.com<mailto:caerhmt3chufva2ek_aidprwktjvk5qelhuzkyrvvxknzjdo...@mail.gmail.com>> Content-Type: text/plain; charset="UTF-8" Dear Gopal, Maybe you can look into MCMCglmm? MCMCglmm can take a lot of error distributions into account. thanks, Manabu On 15 March 2017 at 10:24, Gopal Murali <goopaalmur...@gmail.com<mailto:goopaalmur...@gmail.com>> wrote: > Dear list, > I am trying to fit a regression model using a dataset containing > dependent variable as a percentage (arcsine transformed) and a > categorical independent variable controlled for phylogeny using PGLS. > Following the post below, I found the normality of the residuals to be > non-normal as the data is right skewed (zero-inflated). Is there any > way to overcome this issue? > http://blog.phytools.org/2013/02/a-comment-on-distribution- > of-residuals.html > > Thanks in advance, > Gopal Murali > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-phylo mailing list - > R-sig-phylo@r-project.org<mailto: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-ph...@r-project.org/<mailto:sig-ph...@r-project.org/> > __________________________________________________________________________ This email message is for the sole use of the intended r...{{dropped:9}} _______________________________________________ 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/