This is a repost of an earlier question, after my colleague helped me with
my English:
To calculate signal in PGLS multiple regression (with say two independent
variables) I can use the following model:
lambdaModel <- gls(Y ~ X + bodymass, correlation=corPagel(1, tree),
method="ML")
This will take account of body mass when assessing the strength of
relationship between Y and X. This calculates lambda for the residuals and
is better than calculating lambda for each trait (according to Revell,
2010). My question is, If I only want to find phylogenetic signal in one
(unscaled) variable, should I use the model:
lambdaModel <- gls(Y ~ bodymass, correlation=corPagel(1, tree), method="ML")
Will this give the lambda value for Y after controlling for body mass? Or,
would it be better to 'correct' for body mass first, using a ratio (Y /
body mass), and then calculate lambda for this scaled trait, using for
example:
lambdaModel <- fitContinuous(tree, scaled_Y, model="lambda")
kind regards,
Alberto
[[alternative HTML version deleted]]
_______________________________________________
R-sig-phylo mailing list
R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
