[R] TukeyHSD for multiple response

[Sergio Ferreira Cardoso]

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" <friendly using yorku.ca>
> Para: "Sergio Ferreira Cardoso" <sergio.ferreira-cardoso using umontpellier.fr>, "R-help list" <r-help using 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
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