If you have multiple measurements per species (multiple individuals of a
species, to represent a single tip), there is a program Rphylopars that is now
available, that accounts for within-species variation.
Though maybe it’s not appropriate for your data, as Liam was saying.
I like it, but I would love to hear from those individuals here that are much
more qualified than I am…
> On Jan 27, 2017, at 12:00 PM, Liam J. Revell <liam.rev...@umb.edu> wrote:
> Hi Philip.
> Do not create very short tips. This will actually lead to very high weight
> being given to any difference between these two observations! Take the
> average of the different observations. Using the methods of Felsenstein
> (2008) or Ives & Garland (2007) it is also possible to take into account
> within-species sampling error, though this is not precisely what you have
> here (you do not know how uncertain each measure is, nor how uncertain are
> your estimates for other species), nor is this implemented in R.
> All the best, Liam
> Liam J. Revell, Associate Professor of Biology
> University of Massachusetts Boston
> web: http://faculty.umb.edu/liam.revell/
> email: liam.rev...@umb.edu
> blog: http://blog.phytools.org
> On 1/27/2017 11:45 AM, Philip Shirk wrote:
>> I know this is a repeat question (
>> http://firstname.lastname@example.org/msg04424.html) but I
>> didn't see any reponses/answers to the first posting, so I thought I'd ask
>> I have a pre-published tree for my species of interest that includes all
>> the species in my dataset. However, my dataset contains duplicate data for
>> a few species (different estimates from different authors). What is the
>> best way to incorporate all the data into a PGLS analysis? When I try to
>> run the analysis with gls() I get the error:
>> "Error in Initialize.corPhyl(X[[i]], ...) : number of observations and
>> number of tips in the tree are not equal."
>> I imagine that I could:
>> 1. toss out duplicates
>> 2. average/combine duplicates
>> 3. create very short branches for duplicate species and treat them as very
>> closely-related but separate species (but I don't know how to actually do
>> 4. ???
>> Philip Shirk
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