Re: [R-sig-phylo] aov.phylo vs phylANOVA

[Jacob Berv]

Sorry— I meant aov.phylo (geiger function), not phly.aov. 
J

> On Nov 15, 2018, at 3:00 PM, Jacob Berv  
> wrote:
> 
> Hi everyone — 
> It seems like the solution is that I was looking at the wrong p-value, as is 
> often the case!
> 
> From Liam:
> "The issue may be that you need to look at the p-value from the internal 
> print-out of aov.phylo not from the summary."
> 
> I was using the summary() function to examine the model output from geiger. 
> When applying this function to the phyl.aov output object, the p-values 
> appear to be from a regular anova, not the phylogenetic anova. To access the 
> phylogenetic anova p value, you have to look inside the object generated by 
> phyl.aov:
> 
> attr(obj, ’summary’)
> 
> This will display the appropriate "Pr(>F) given phy"
> 
> Jake
> 
> 
>> On Nov 15, 2018, at 12:53 PM, Liam J. Revell  wrote:
>> 
>> Hi Jacob.
>> 
>> As far as I know, aov.phylo and phylANOVA should be doing more or less the 
>> same thing. With random data if I run enough simulations for the null 
>> distribution of F the P-values of the two different implementations come out 
>> almost exactly the same. One difference that I noted is that if you give 
>> either method data vectors without taxon names both work, but only phylANOVA 
>> gives a warning.
>> 
>> Please send along the data that has generated this incongruency if you are 
>> unable to figure it out.
>> 
>> All the best, Liam
>> 
>> Liam J. Revell
>> Associate Professor, University of Massachusetts Boston
>> Profesor Asistente, Universidad Católica de la Ssma Concepción
>> web: http://faculty.umb.edu/liam.revell/, http://www.phytools.org
>> 
>> On 11/15/2018 2:30 PM, Jacob Berv wrote:
>>> Dear R-sig-phylo,
>>> I was wondering if anyone on here might be able to help me understand the 
>>> difference between phytool’s implementation of phylogenetic ANOVA and 
>>> geiger’s implementation. From the respective documentation, it seems that 
>>> both approaches rely on and cite the same reference:
>>> Garland T Jr, AW Dickerman, CM Janis, and JA Jones. 1993. Phylogenetic 
>>> analysis of covariance by computer simulation. Systematic Biology 
>>> 42(3):265-292.
>>> Both seem to have a similar approach, at least as it is described in their 
>>> respective documentations, and both seem to rely on character simulations 
>>> to derive their p values. It seems aov.phylo uses sim.char() and phylANOVA 
>>> uses fastBM() for their simulations internally.
>>> On Liam’s blog, he indicates that these tests are the same, except that 
>>> phylANOVA additionally performs post-hoc tests.
>>> http://blog.phytools.org/2013/02/updated-phylanova.html
>>> However, running some of my data through both of these tests is generating 
>>> totally different results (aov.phylo detecting significant differences 
>>> where phylANOVA does not, with p values differing by 5 orders of magnitude.
>>> Running my same test data~group through a pgls also generates a result 
>>> comparable to what I get from phylANOVA — so it seems like perhaps 
>>> aov.phylo is the outlier?
>>> Best,
>>> Jake Berv
>>> ___
>>> 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/
> 

___
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/

Re: [R-sig-phylo] aov.phylo vs phylANOVA

[Jacob Berv]

Hi everyone — 
It seems like the solution is that I was looking at the wrong p-value, as is 
often the case!

>From Liam:
"The issue may be that you need to look at the p-value from the internal 
print-out of aov.phylo not from the summary."

I was using the summary() function to examine the model output from geiger. 
When applying this function to the phyl.aov output object, the p-values appear 
to be from a regular anova, not the phylogenetic anova. To access the 
phylogenetic anova p value, you have to look inside the object generated by 
phyl.aov:

attr(obj, ’summary’)

This will display the appropriate "Pr(>F) given phy"

Jake


> On Nov 15, 2018, at 12:53 PM, Liam J. Revell  wrote:
> 
> Hi Jacob.
> 
> As far as I know, aov.phylo and phylANOVA should be doing more or less the 
> same thing. With random data if I run enough simulations for the null 
> distribution of F the P-values of the two different implementations come out 
> almost exactly the same. One difference that I noted is that if you give 
> either method data vectors without taxon names both work, but only phylANOVA 
> gives a warning.
> 
> Please send along the data that has generated this incongruency if you are 
> unable to figure it out.
> 
> All the best, Liam
> 
> Liam J. Revell
> Associate Professor, University of Massachusetts Boston
> Profesor Asistente, Universidad Católica de la Ssma Concepción
> web: http://faculty.umb.edu/liam.revell/, http://www.phytools.org
> 
> On 11/15/2018 2:30 PM, Jacob Berv wrote:
>> Dear R-sig-phylo,
>> I was wondering if anyone on here might be able to help me understand the 
>> difference between phytool’s implementation of phylogenetic ANOVA and 
>> geiger’s implementation. From the respective documentation, it seems that 
>> both approaches rely on and cite the same reference:
>> Garland T Jr, AW Dickerman, CM Janis, and JA Jones. 1993. Phylogenetic 
>> analysis of covariance by computer simulation. Systematic Biology 
>> 42(3):265-292.
>> Both seem to have a similar approach, at least as it is described in their 
>> respective documentations, and both seem to rely on character simulations to 
>> derive their p values. It seems aov.phylo uses sim.char() and phylANOVA uses 
>> fastBM() for their simulations internally.
>> On Liam’s blog, he indicates that these tests are the same, except that 
>> phylANOVA additionally performs post-hoc tests.
>> http://blog.phytools.org/2013/02/updated-phylanova.html
>> However, running some of my data through both of these tests is generating 
>> totally different results (aov.phylo detecting significant differences where 
>> phylANOVA does not, with p values differing by 5 orders of magnitude.
>> Running my same test data~group through a pgls also generates a result 
>> comparable to what I get from phylANOVA — so it seems like perhaps aov.phylo 
>> is the outlier?
>> Best,
>> Jake Berv
>> ___
>> 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/

___
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/

Re: [R-sig-phylo] aov.phylo vs phylANOVA

[Liam J. Revell]

Hi Jacob.

As far as I know, aov.phylo and phylANOVA should be doing more or less 
the same thing. With random data if I run enough simulations for the 
null distribution of F the P-values of the two different implementations 
come out almost exactly the same. One difference that I noted is that if 
you give either method data vectors without taxon names both work, but 
only phylANOVA gives a warning.


Please send along the data that has generated this incongruency if you 
are unable to figure it out.


All the best, Liam

Liam J. Revell
Associate Professor, University of Massachusetts Boston
Profesor Asistente, Universidad Católica de la Ssma Concepción
web: http://faculty.umb.edu/liam.revell/, http://www.phytools.org

On 11/15/2018 2:30 PM, Jacob Berv wrote:

Dear R-sig-phylo,
I was wondering if anyone on here might be able to help me understand the 
difference between phytool’s implementation of phylogenetic ANOVA and geiger’s 
implementation. From the respective documentation, it seems that both 
approaches rely on and cite the same reference:

Garland T Jr, AW Dickerman, CM Janis, and JA Jones. 1993. Phylogenetic analysis 
of covariance by computer simulation. Systematic Biology 42(3):265-292.

Both seem to have a similar approach, at least as it is described in their 
respective documentations, and both seem to rely on character simulations to 
derive their p values. It seems aov.phylo uses sim.char() and phylANOVA uses 
fastBM() for their simulations internally.

On Liam’s blog, he indicates that these tests are the same, except that 
phylANOVA additionally performs post-hoc tests.
http://blog.phytools.org/2013/02/updated-phylanova.html

However, running some of my data through both of these tests is generating 
totally different results (aov.phylo detecting significant differences where 
phylANOVA does not, with p values differing by 5 orders of magnitude.

Running my same test data~group through a pgls also generates a result 
comparable to what I get from phylANOVA — so it seems like perhaps aov.phylo is 
the outlier?

Best,
Jake Berv
___
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/



___
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/

Re: [R-sig-phylo] aov.phylo vs phylANOVA

[Theodore Garland]

As the lead author of the paper in question, I'll be curious to find out
what you uncover.

Thanks and cheers,
Ted


Theodore Garland, Jr., Distinguished Professor

Department of Evolution, Ecology, and Organismal Biology (EEOB)

University of California, Riverside

Riverside, CA 92521

Office Phone:  (951) 827-3524

Facsimile:  (951) 827-4286 (not confidential)

Email:  tgarl...@ucr.edu

http://www.biology.ucr.edu/people/faculty/Garland.html

http://scholar.google.com/citations?hl=en=iSSbrhwJ


Director, UCR Institute for the Development of
Educational
Applications 


Editor in Chief, *Physiological and Biochemical Zoology
*


Fail Lab: Episode One

*https://www.youtube.com/watch?v=c0msBWyTzU0
*

On Thu, Nov 15, 2018 at 9:30 AM, Jacob Berv 
wrote:

> Dear R-sig-phylo,
> I was wondering if anyone on here might be able to help me understand the
> difference between phytool’s implementation of phylogenetic ANOVA and
> geiger’s implementation. From the respective documentation, it seems that
> both approaches rely on and cite the same reference:
>
> Garland T Jr, AW Dickerman, CM Janis, and JA Jones. 1993. Phylogenetic
> analysis of covariance by computer simulation. Systematic Biology
> 42(3):265-292.
>
> Both seem to have a similar approach, at least as it is described in their
> respective documentations, and both seem to rely on character simulations
> to derive their p values. It seems aov.phylo uses sim.char() and phylANOVA
> uses fastBM() for their simulations internally.
>
> On Liam’s blog, he indicates that these tests are the same, except that
> phylANOVA additionally performs post-hoc tests.
> http://blog.phytools.org/2013/02/updated-phylanova.html
>
> However, running some of my data through both of these tests is generating
> totally different results (aov.phylo detecting significant differences
> where phylANOVA does not, with p values differing by 5 orders of magnitude.
>
> Running my same test data~group through a pgls also generates a result
> comparable to what I get from phylANOVA — so it seems like perhaps
> aov.phylo is the outlier?
>
> Best,
> Jake Berv
> ___
> 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-ph...@r-project.org/
>

[[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/

[R-sig-phylo] aov.phylo vs phylANOVA

[Jacob Berv]

Dear R-sig-phylo,
I was wondering if anyone on here might be able to help me understand the 
difference between phytool’s implementation of phylogenetic ANOVA and geiger’s 
implementation. From the respective documentation, it seems that both 
approaches rely on and cite the same reference:

Garland T Jr, AW Dickerman, CM Janis, and JA Jones. 1993. Phylogenetic analysis 
of covariance by computer simulation. Systematic Biology 42(3):265-292.

Both seem to have a similar approach, at least as it is described in their 
respective documentations, and both seem to rely on character simulations to 
derive their p values. It seems aov.phylo uses sim.char() and phylANOVA uses 
fastBM() for their simulations internally. 

On Liam’s blog, he indicates that these tests are the same, except that 
phylANOVA additionally performs post-hoc tests. 
http://blog.phytools.org/2013/02/updated-phylanova.html

However, running some of my data through both of these tests is generating 
totally different results (aov.phylo detecting significant differences where 
phylANOVA does not, with p values differing by 5 orders of magnitude. 

Running my same test data~group through a pgls also generates a result 
comparable to what I get from phylANOVA — so it seems like perhaps aov.phylo is 
the outlier?

Best,
Jake Berv
___
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/