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. -- Institut des Sciences de l'Evolution UMR5554, CNRS, IRD, EPHE Université de Montpellier Place Eugène Bataillon 34095 Montpellier Cedex 05 France Email: [email protected] Tel: +33 (4 ) 67 14 46 52 [[alternative HTML version deleted]] ______________________________________________ [email protected] 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.
