Quick correction: index variables are transformed into n x (k - 1) matrices of INDICATOR variables.
On Wed, Feb 4, 2015 at 5:25 PM, Peter Smits <psm...@uchicago.edu> wrote: > Hi Will, > > Quick answer to that question: yes. > > The key is that categorical variables cannot be modeled directly in a GLM > framework. These categorical variables, or index variables, are transformed > into n x (k - 1) matrices of index variables. These index variables are > binary where a 1 corresponds to the observed having that state. K is the > number of states in the index variable. Only k - 1 columns are necessary > because the intercept of the model corresponds to the remaining state. The > interpretation of the beta coefficients for each of the (k - 1) predictors > are then their contrast to or difference between that state and the state > "held" by the intercept. > > R will do this silently when you fit the model. > > If all k states are included while also including an intercept term, the > model becomes unidentifiable because you've effectively included two > intercept terms which are additively non-identifiable. > > I hope that makes sense. > > Cheers, > > Peter > > On Wed, Feb 4, 2015 at 5:20 PM, William Gearty <wgea...@stanford.edu> > wrote: > >> Hi Liam, >> >> Thanks for the help! >> Does this type of linear model work if X1 and X2 are categorical >> variables? >> >> -Will >> >> On Wed, Feb 4, 2015 at 2:48 PM, Liam J. Revell <liam.rev...@umb.edu> >> wrote: >> >> > Hi William. >> > >> > You should be able to fit this kind of model using gls in the nlme >> > package. In your case, this would look something like: >> > >> > library(ape) >> > library(nlme) >> > fit<-gls(Y~X1*X2,data,correlation=corBrownian(1,tree)) >> > anova(fit) >> > >> > for instance. This is just a linear model with multiple predictors and >> > residual error that is correlated according to the phylogeny. >> > >> > If you search R-sig-phylo for gls and/or nlme, or search the web for GLS >> > and phylogenies, you should be able to find out more info. >> > >> > 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 2/4/2015 5:38 PM, William Gearty wrote: >> > >> >> Apologies if this has been asked before... >> >> I'm trying to perform a phylogenetic ANOVA with multiple predictors. >> >> I'm able to do a normal ANOVA with multiple predictors like this: >> >> >> >> aov(Y ~ X1 * X2, data) >> >>> >> >> >> >> However, I'd like to account for phylogenetic relatedness and tried >> doing >> >> something similar with aov.phylo: >> >> >> >> aov(Y ~ X1 * X2, phy) >> >>> >> >> >> >> However, the function yells at me: >> >> >> >> 'formula' must be of the form 'dat~group', where 'group' is a named >> >>> factor >> >>> vector and 'dat' is a data matrix or named vector >> >>> >> >>> Therefore, it seems like aov.phylo is not built to perform a >> >> multi-predictor analysis like the normal aov function is. >> >> Are there any similar functions that would be able pull this off? Is >> there >> >> way around this with aov.phylo? >> >> Any thoughts would be greatly appreciated, >> >> Will >> >> >> >> >> >> >> -- >> William Gearty >> PhD Student, Paleobiology >> Department of Geological and Environmental Sciences >> Stanford School of Earth Sciences >> people.stanford.edu/wgearty >> >> [[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/ >> > > > > -- > Peter D Smits > Grad student > Committee on Evolutionary Biology > University of Chicago > psm...@uchicago.edu > http://home.uchicago.edu/~psmits/home.html > -- Peter D Smits Grad student Committee on Evolutionary Biology University of Chicago psm...@uchicago.edu http://home.uchicago.edu/~psmits/home.html [[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/
