Michael, Thank you very much for your answer. I finally tried lsmeans to compare what I wanted. I'll follow your advice and explore the CDA. It's probably a better solution to assess what I want.
Best, Sérgio. ----- Mensagem original ----- > De: "Michael Friendly" <frien...@yorku.ca> > Para: "Sergio Ferreira Cardoso" <sergio.ferreira-card...@umontpellier.fr>, > "R-help list" <r-help@r-project.org> > Enviadas: Sábado, 26 De Maio de 2018 17:28:20 > Assunto: Re: TukeyHSD for multiple response > Hi Sergio > > Doing those tests 30 times is going to give you a huge Type I error > rate, even if there was a function that did that. There is a reason > why TukeyHSD doesn't make it easy. > > In general, if there are useful comparisons among the species, you are > better off setting up and testing contrasts than doing all-pairwise > Tukey tests. > > Also, the PCA scores are ordered in terms of variance acct'd for, so > maybe only the first few are important. > > Finally, you might be better off using Canonical Discriminant analysis > than PCA followed by MANOVA. The candisc package is well suited to this > task. It can give you HE plots in the space that best discriminates > among the levels of an effect, and show how the original variables > relate to (project into) that space. > CDA is sort of like PCA, but the goal is to account for maximum > differences among groups rather than maximum total variance. > > For proper partial Type III tests, use car::Manova rather than stats::manova > which only gives sequential, Type I tests > > HTH > -Michael > > On 5/25/2018 9:11 AM, Sergio Ferreira Cardoso wrote: >> Dear all, >> >> I'm testing the effect of species and sex in my sample by using the principal >> component scores of a PCA analysis. >> I have 30 PCs and I tried to see if there is any significant difference from >> males to females, given that there is a significant effect of phylogeny >> (factor >> with several species). >> I didi it like this: >> >> Y<-PCA$pc.scores[,1:30] >> fit <- manova(Y ~ sp*sex) >> summary(fit, test="Wilks") >> >> I get a barely significant p-value for the effect of sex and I'd like to know >> for which of the species there is a difference between males and females. >> I tried TukeyHSD(fit) but I get the following error: >> >> Error in model.tables.aov(x, "means") : >> 'model.tables' is not implemented for multiple responses >> >> So this has to do with the fact that I have a multivariate independent >> variable. >> Is there an alternative function to this? >> >> Thanks in advance, >> Sérgio. >> > > > -- > Michael Friendly Email: friendly AT yorku DOT ca > Professor, Psychology Dept. & Chair, ASA Statistical Graphics Section > York University Voice: 416 736-2100 x66249 Fax: 416 736-5814 > 4700 Keele Street Web: http://www.datavis.ca > Toronto, ONT M3J 1P3 CANADA ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.