Hi all, I’m using OUwie to fit multi-optima OU models and I have a question about incorporating measurement error into my analyses.
I’m running my models with known measurement error (mserr=‘known’) and using the standard error (std.error()) as an estimate of it, as recommended by Ives et al (2007). However, for some (a minority) of my tips, I was only able to measure 1 specimen, so I have no standard error for them. So I’m not sure about how to deal with those. At first I thought about just setting their measurement error as 0, but then I figured that would introduce false confidence. So what I’m doing now is I’m setting measurement error for those tips as the mean of the errors of all the tips for which I did measure more than one specimen. I got that idea also from Ives et al when they mention averaging the error across species (jn the third-to-last paragraph), but that was in a different context. I can’t find any references that report dealing with the same problem, even though I assume it must not be an uncommon one. So I’m wondering if mine is really the best way to do it and, or if anyone has alternative suggestions? i hope I’ve made my problem clear, and thanks in advance for any suggestions. *--* *Rafael Sobral Marcondes* PhD Candidate (Systematics, Ecology and Evolution/Ornithology) Museum of Natural Science <http://sites01.lsu.edu/wp/mns/> Louisiana State University 119 Foster Hall Baton Rouge, LA 70803, USA Twitter: @rafmarcondes <https://twitter.com/rafmarcondes> [[alternative HTML version deleted]] _______________________________________________ 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/
