Re: [R-sig-phylo] phylogenetic signal with sample sizes but no standard errors

2017-08-04 Thread Emmanuel Paradis

There is also an implementation of this method in two functions in ape, see:

?pic.ortho
?varCompPhylip

There are examples with simulated data in both help pages. The second 
function requires PHYLIP (similarly to Rphylip)	.


Best,

Emmanuel

Le 04/08/2017 à 14:36, Joe Felsenstein a écrit :

There is also my C program Contrast, which implements a method from a
2008 paper I wrote:

Felsenstein, J.  2008.  Comparative methods with sampling error and
within-species variation: contrasts revisited and revised. American
Naturalist 171: 713-725.

This estimates the within-species covariances and the between-species
evolutionary variances.It is not an R program but can be accessed
through Liam Revell's package Rphylip, if you also have my (non-R)
package PHYLIP installed.

A pretty good (but not ML) estimate of the within-species phenotypic
variance can be gotten by pooling the within-species sampling error.
The harder part is using that to correct one's estimate of the
covariances of the between-species change, which using ordinary
methods will have some within-species variation mixed in.

Joe

Joe Felsenstein j...@gs.washington.edu
  Department of Genome Sciences and Department of Biology,
  University of Washington, Box 355065, Seattle, WA 98195-5065 USA

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Re: [R-sig-phylo] phylogenetic signal with sample sizes but no standard errors

2017-08-04 Thread Joe Felsenstein
There is also my C program Contrast, which implements a method from a
2008 paper I wrote:

Felsenstein, J.  2008.  Comparative methods with sampling error and
within-species variation: contrasts revisited and revised. American
Naturalist 171: 713-725.

This estimates the within-species covariances and the between-species
evolutionary variances.It is not an R program but can be accessed
through Liam Revell's package Rphylip, if you also have my (non-R)
package PHYLIP installed.

A pretty good (but not ML) estimate of the within-species phenotypic
variance can be gotten by pooling the within-species sampling error.
The harder part is using that to correct one's estimate of the
covariances of the between-species change, which using ordinary
methods will have some within-species variation mixed in.

Joe

Joe Felsenstein j...@gs.washington.edu
 Department of Genome Sciences and Department of Biology,
 University of Washington, Box 355065, Seattle, WA 98195-5065 USA

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Re: [R-sig-phylo] phylogenetic signal with sample sizes but no standard errors

2017-08-02 Thread Theodore Garland
The original paper is here, with Matlab code.  Others can tell you where
this is in R.

Ives, A. R., P. E. Midford, and T. Garland, Jr. 2007. Within-species
variation and measurement error in phylogenetic comparative methods.
Systematic Biology 56:252–270.

Cheers,
Ted

On Wed, Aug 2, 2017 at 7:50 AM, Vincenzo Ellis 
wrote:

> Dear list users,
>
> I'm interested in testing for phylogenetic signal in a trait of parasites:
> the number of host species a parasite infects. I have a phylogeny for the
> parasites and I have tabulated the number of host species each parasite
> infects from the literature. However, some parasites are well sampled
> (estimates from 20+ studies) and many are poorly sampled (estimates from
> one study). So I would like to incorporate sampling error into the
> calculation.
>
> I know that the phylosig function in phytools can do this, but it's not
> clear to me how to estimate appropriate standard errors for these data.
>
> In the literature, people have dealt with this by testing for phylogenetic
> signal in the residuals of a regression between number of host species a
> parasite infects and the number of studies of the parasite.
>
> I'm wondering if there is another way to go about it, perhaps by weighting
> species by sample size in the calculation of phylogenetic signal. Does
> anyone know of a way to do something like this? Or do you think my best bet
> is to just work with the residuals from a regression with sample size?
>
> Thanks for any feedback!
>
> Vincenzo
>
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>
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