Dear Karla,
I think you can perform this type of analysis using a multivariate �repeated 
measures� design, considering the male and female as separate (responses) 
traits to be correlated to your covariates. You can then use generalized 
hypothesis testing with contrasts coding.
In mvMORPH, for instance, you can use a model such as:
fit <- mvgls(cbind(male, female) ~ correlate1 + correlate2, tree=tree, 
model=�lambda�, method=�LL�)
You can then test the 'global' effect using the �manova.gls� function to test 
the predictors
manova.gls(fit) # overall test - any significant effect of both predictors ?
To further assess whether there are differences between sexes, you can use 
contrast coding:
P = matrix(c(1,-1), ncol=1) # compare the male to the female �response� 
variables
L1 = c(0,1,0) # test whether the first correlate shows any differences between 
sexes
manova.gls(fit, P=P, L=L1)
L2 =c(0,0,1) # to test for a different effect of the correlate2 between sexes.
manova.gls(fit, P=P, L=L2)
In brief, the contrast code 'P' is used to compare the male and female traits 
(it takes their differences), while the contrast code 'L' tests whether the 
slope of both predictors is different from zero (i.e., it tests whether there�s 
a significant difference in the relationship with the predictors between males 
and females while taking into account the correlation between both traits and 
controlling for the phylogenetic relationships). More formally, this 
generalized linear hypothesis tests whether L%*%coef(fit)%*%P = 0 and reject it 
(p-values<0.05) otherwise.
Hope this helps.
Best regards,
Julien

________________________________
De : R-sig-phylo <[email protected]> de la part de Emmanuel 
Paradis <[email protected]>
Envoy� : lundi 26 mai 2025 18:50
� : Karla Shikev <[email protected]>
Cc : R Sig Phylo Listserv <[email protected]>
Objet : Re: [R-sig-phylo] PGLS with two values per tip

Dear Karla,

I think the question was discussed on this list some years ago but I don't 
remember the details -- a search in the archives could help you.

Surely, 'sex' is not a (species-level) evolving trait. Maybe try to analyse 
'sexual dimorphism' if the trait is present in both sexes. If the trait is 
present in only one sex (e.g., antler size), I think a good approach would be 
to analyse males/females separately.

Best,

Emmanuel

----- Le 21 Mai 25, � 21:14, Karla Shikev [email protected] a �crit :

> Dear all,
>
> I'm trying to do an analysis that is a bit unusual and I'd appreciate any
> feedback. I'm looking at correlates of body size, but I want to analyze
> males and females separately. However, a regular PGLS would only allow one
> value per tip. I'd like something like this:
>
> body size ~ correlate1 + correlate2 + sex
>
> Any suggestions?
>
> Karla
>
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