Hi all,
I am running a number of PGLS regressions, some of which are multiple
regressions. I am using the nlme package with the corBrownian error
structure. If I build a model M via multiple regression, then I can get a
summary of the model that includes p values as well as a number of other
statistics. But how can I get an overall p-value for this model?
In the same vein, as value, std. error, t-value and p-value are all
returned for each of the traits separately, what does one report for
multiple regression models? I have been unable to find a paper that
actually reported this type of information for such a model.
Here is a toy example:
require(nlme)
require(phytools)
tree <- pbtree(n=20)
dat <- as.data.frame(fastBM(tree, nsim=4))
colnames(dat) <- paste('trait', 1:4, sep='')
M <- gls(trait1 ~ trait2 + trait3 + trait4, data=dat,
correlation=corBrownian(1, tree))
summary(M)
Any help/advice would be greatly appreciated. Thanks!
-Pascal
--
Pascal Title
PhD candidate, Rabosky Lab
<http://www-personal.umich.edu/~drabosky/Home.html>
Dept of Ecology and Evolutionary Biology
University of Michigan
pti...@umich.edu
pascaltitle.weebly.com
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