If the "regressions" are being done in a model which implies that the two variables are multivariate normal, then we can simply estimate the parameters of that joint distribution, which are of course the two means and the three elements of the covariance matrix.
If we then test whether Cov(X,Y) is different from zero, that should be equivalent to a test of significance of either regression. /* crankiness on */ Note of course that most "phylogenetic" regressions are being done wrong: if they assume that Y responds to the current value of X, but when the value of Y may actually be the result of optimum selection which is affected by past values of X which we do not observe directly. I've complained about this here in the past, to no avail, Thomas Hansen, in a recent paper, made the same point, with evidence too. /* crankiness off */ J.F. ---- Joe Felsenstein j...@gs.washington.edu Department of Genome Sciences and Department of Biology, University of Washington, Box 355065, Seattle, WA 98195-5065 USA _______________________________________________ R-sig-phylo mailing list - R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
