Hi,
Regarding the blog and the feasibility of MCMCglmm for threshold models:
If y1 is binary and y2 is normal, then the univariate analysis would be:
Ainv<-inverseA(tree)$Ainv
m1<-MCMCglmm(y1~y2, random=~species,ginverse=list(species=Ainv),
data=my.data, prior=my.prior, family="ordinal")
f
Theodore Garland Jr wrote:
> Check this:
>
> Ives, A. R., and T. Garland, Jr. 2010. Phylogenetic logistic regression for
> binary dependent variables. Systematic Biology 59:9-26.
In addition, check this:
Felsenstein, J. 2012. A comparative method for both discrete and continuous
characters
Hi Jordan.
One option is to use the threshold model from quantitative genetics and
estimate the evolutionary correlation/covariance between the binary
trait and the continuous characters. This approach is described in
Felsenstein (2012; Am. Nat.) and implemented in the stand-alone C
program,
Check this:
Ives, A. R., and T. Garland, Jr. 2010. Phylogenetic logistic regression for
binary dependent variables. Systematic Biology 59:9-26.
Cheers,
Ted
Theodore Garland, Jr.
Professor
Department of Biology
University of California, Riverside
Riverside, CA 92521
Office Phone: (951) 827-3524
