Dear Rafael.

`I believe the standard errors are computed from (negative inverse of)`

`the Hessian matrix - which is a matrix containing the second-order`

`partial derivatives (or some numerical approximation of them) from the`

`likelihood surface.`

`These values are measurements of the curvature of the likelihood`

`surface. If the likelihood surface is highly curved (downwards, that is`

`negatively) then this means that the ML solution is much more likely`

`than other nearby possibilities, and the negative inverse of this value`

`is a small quantity - indicating little variance (i.e., uncertainty) in`

`the estimated parameter. Conversely, a large standard error (the square`

`of which is the variance) indicates that the likelihood surface is very`

`flat (that is, it has a very small negative curvature) around the ML`

`solution.`

`In your particular case broadly overlapping CIs for the parameter`

`estimates (which can be computed as theta+-1.96*SE) of theta probably`

`mean that the 'adaptive peaks' of different regimes can't be`

`distinguished one from the other; whereas a CI for alpha that included`

`zero (for instance) might suggest that a BM model probably better fits`

`the data.`

All the best, Liam Liam J. Revell, Associate Professor of Biology University of Massachusetts Boston & Profesor Asociado, Programa de BiologĂa Universidad del Rosario web: http://faculty.umb.edu/liam.revell/ On 4/4/2018 2:30 PM, Rafael S Marcondes wrote:

Dear all,I'm writing (again!) to ask for help interpreting standard errors ofparameter estimates in OUwie models.I'm using OUwie to examine how the evolution of bird plumage colorvaries across habitat types (my selective regimes) in a tree of 229tips. I was hoping to be able to make inferences based on OUMV and OUMVAmodels, but I was getting nonsensical theta estimates from those. SoI've basically given up on them for now.But even looking at theta estimates from OUM models, I'm getting reallylarge standard errors, often overlapping the estimates from otherselective regimes. So I was wondering what that means exactly. How arethese erros calculated? How much do high errors it limit the biologicalinferences I can make? I'm more interested in the relative thetas acrossregimes than on the exact values (testing the prediction that birds indarker habitats tend to adapt to darker plumages than birds in moreilluminated habitats).I have attached a table averaging parameter estimates and errors frommodels fitted across a posterior distribution of 100 simmaps for fourtraits; and one exemplar fitted model from one trait in one of thosesimmaps.Thanks a lot for any help, *-- * *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: @brown_birds <https://twitter.com/brown_birds> _______________________________________________ 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/

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