Hi Everyone,
I agree with what has been said so far. Tony, don't take my comments to
heart. Your contribution is most welcome as your opinion is highly
respected (by me and hopefully by others). Same goes for all the other
authorities on the list e.g Liam, Joe, Ben, Jarrod, Ted, Marguerite and
others. I don't contribute much these days due to time constraints,
which is a shame because I think that lists like this do help people,
even if particular answers to particular questions are not quite right
or are incomplete in some sense for the original poster. And I like
helping people too! Questions can get answers that evolve into
interesting threads in their own right (like this one, although a bit
off-topic). Mailing lists like this are more of a group conversation
rather than a simple "do this" or "don't do that" type of thing. I've
been on lists since the '90s (does anyone remember sci.bio.evolution on
USENET?). This is one of the best lists I've been on, largely because I
know that some of the best researchers in the field read the list and
sometimes respond.
Tony, I know that statistical advice is easier to give when the person
and data are live right in front of you. That's why I invariably only
see people by appointment when I give stats advice. I don't like giving
advice over email and I don't give advice over the phone. (Actually, I
never answer my phone but that's another story.) It's a bit different on
the list because other authorities can read the advice an chime in if
they disagree with anything I say. Hopefully we can all benefit from that.
Keep on posting everybody!
Simon.
On 03/03/15 03:43, Hilmar Lapp wrote:
+100 !!
-hilmar
On 3/2/15, 11:07 AM, David Bapst wrote:
Off-topic, but I wanted to comment on Anthony's wariness about
commenting on R-sig lists...
Yes, it can certainly be very difficult to give advice that is
tailored specifically to the problem of a particular worker on R-sig
lists, particularly as one can't just tell the other person to open
their data files and show them to you. However, answering a question
on R-sig lists (regardless of whether it is the right answer, but what
answer remains right forever anyway?) records that answer virtually
forever, for future posterity. This means the answer can be found by
any future individuals who encounter this problem, via a simple google
search. Since I first found R-sig-phylo in early 2010 (five years
ago!), I have made almost constant use of the knowledge base contained
with R-sig-phylo's archive. It doesn't mean the information is always
right, or always the best answers for the actual person who asked
originally, but it certainly helps point out the right line of
thinking or the right literature to investigate. StackExchange
discussion archives have become just as valuable (but there appears to
be very little R phylo discussion over there).
It feels like the amount of discussion on the list has dropped off
slowly over the last year, and as phylogenetics in R seems as widely
used as ever, I have often wondered if this reflects that most issues
people may run into are now more easily solved with google searches
leading to the R-sig-phylo archives.
Anyway, I just hope that this element is not forgotten about why I
think replying to question on R-sig-phylo remains a valuable
contribution to our community!
Cheers,
-Dave Bapst
On Mon, Mar 2, 2015 at 7:58 AM, Anthony Ives <ari...@wisc.edu> wrote:
Simon and Ben,
Of course, sample size of 8 is going to be an issue in almost any
analysis. But sometimes that is all the data there are.
Incidentally, this exchange reminded me that I’m still wary of making
comments on r-sig. If somebody comes into my office, I have the time to
discuss with them their data, so I can learn more about it. Then I feel
I can at least make informed recommendations for analyses — they might
still be badly wrong recommendations, but at least they are informed.
I’m still uncomfortable about making suggestions on r-sig, when I don’t
really have full information, or the time to think. Therefore, the few
comments I’ve made have been very general about methods, rather than
specific about data sets.
I think this is just a matter of me waking up to the 21st century. I
do like the idea of crowdsourcing; I just need to get comfortable with it.
Cheers, Tony
Anthony Ives
Department of Zoology
459 Birge Hall (4th floor, E end of bldg)
UW-Madison
Madison, WI 53706
608-262-1519
On Mar 1, 2015, at 10:53 PM, Simon Blomberg <s.blombe...@uq.edu.au>
wrote:
Hi Ben,
Yes, you would have to assume constant variance across species to use
N=24. I think that is the only option. But given that biological data
often has a positive mean-variance relationship, again I'm dubious about
the exercise. YMMV, however!
Cheers,
Simon.
Simon Blomberg, BSc (Hons), PhD, MAppStat, AStat.
Senior Lecturer and Consultant Statistician
School of Biological Sciences
The University of Queensland
St. Lucia Queensland 4072
Australia
T: +61 7 3365 2506
email: S.Blomberg1_at_uq.edu.au
http://www.evolutionarystatistics.org
Policies:
1. I will NOT analyse your data for you.
2. Your deadline is your problem
Basically, I'm not interested in doing research and I never have
been. I'm interested in understanding, which is quite a different thing.
- David Blackwell
________________________________________
From: R-sig-phylo [r-sig-phylo-boun...@r-project.org] on behalf of
Ben Bolker [bbol...@gmail.com]
Sent: Monday, March 02, 2015 2:49 PM
To: r-sig-phylo@r-project.org
Subject: Re: [R-sig-phylo] phytools - evaluating significance of
pgls.Ives
On 15-03-01 11:40 PM, Simon Blomberg wrote:
Am I missing something? The OP only has 8 species in the data set.
I wouldn't put much store in fancy PCM modelling based on such a
small data set. And 3 individuals per species is not enough for a
good estimate of the within-species variance.
Simon.
Agree wholeheartedly with the first point -- but for the second,
isn't 24 rather than 8 the relevant number for estimating
within-species variance (since presumably we are assuming the same
variance within every species, thus we can effectively pool
within-species variation \across species for this purpose) ?
Simon Blomberg, BSc (Hons), PhD, MAppStat, AStat. Senior Lecturer
and Consultant Statistician School of Biological Sciences The
University of Queensland St. Lucia Queensland 4072 Australia
T: +61 7 3365 2506 email: S.Blomberg1_at_uq.edu.au
http://www.evolutionarystatistics.org
Policies:
1. I will NOT analyse your data for you. 2. Your deadline is
your problem
Basically, I'm not interested in doing research and I never have
been. I'm interested in understanding, which is quite a different
thing. - David Blackwell
________________________________________ From: R-sig-phylo
[r-sig-phylo-boun...@r-project.org] on behalf of Anthony R Ives
[ari...@wisc.edu] Sent: Monday, March 02, 2015 2:14 PM To: Andrea
Berardi Cc: r-sig-phylo@r-project.org Subject: Re: [R-sig-phylo]
phytools - evaluating significance of pgls.Ives
Andrea,
I second Liam’s recommendation to use a LRT.
For measurement error, the latest code I have in matlab is
MERegPHYSIGv2.m, which does both measurement error and an OU or
Pagel-lambda transform (see Johnson, M. T. J., A. R. Ives, J.
Ahern, and J. P. Salminen. 2014. Macroevolution of plant defenses
against herbivores in the evening primroses. New Phytologist
203:267-279). Measurement-error models are always going to have
difficulties at parameter boundaries; for example, if the assumed
measurement error is large, it can exceed the observed variation in
the data, which of course causes problems (statistical and
logical).
In MERegPHYSIGv2.m, I did a round or two of simulated annealing
first, before polishing the results with a Nelder-Mead optimizer.
It seems like you could do the same with Liam’s code pretty easily
by changing the method of optimization (using edit()). Before
doing this, thought, I would take a careful look at your data and
your estimates of measurement error. An easy diagnostic is to start
with 10% of your estimated measurement standard errors and then
increase slowly to 100%. When I have done this, I’ve been able to
see problems when parameter values go awry. It is not a fail-safe
diagnostic in any way, but it can help.
Cheers, Tony
Anthony Ragnar Ives Department of Zoology UW-Madison Madison, WI
53706 608-262-1519
On Mar 1, 2015, at 9:42 PM, Liam J. Revell <liam.rev...@umb.edu>
wrote:
Hi Andrea.
This is not presently implemented, but since this is a
likelihood method it would be straightforward to constrain to a
slope of zero and then do a LR test. This would be probably be
the easiest way to test a hypothesis about the regression.
That being said, as noted in the function documentation, some
problems have been reported with the optimization algorithm for
this model, which is simple and thus may fail to find the ML
solution. Consequently, I would encourage you to look for other
implementations of the method so that you can be confident in
your result. I'm not aware of one in R at this time.
All the best, Liam
Liam J. Revell, Assistant 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 3/1/2015 10:31 PM, Andrea Berardi wrote:
Hi all,
I'm just learning how to do PGLS analyses, and I'm looking for
advice on how to evaluate the significance of the regression
fit using pgls.Ives in the phytools package. I'm using this
function because it incorporates sampling error of species
means, and my data has about 3 individuals per species, with 8
species. My goal is to test whether a flower trait predicts the
leaf trait, while controlling for shared ancestry. Here is the
output from pgls.Ives:
fit <- pgls.Ives(Tree, Flower_trait, Leaf_trait) fit
$beta [1] 96.3963098 0.1292656
$sig2x [1] 22218901073
$sig2y [1] 23027587
$a [1] -10063.150 -1204.422
$logL [1] -158.2337
$convergence [1] 0
$message [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"
I am also running pgls on species averages for the traits
using the gls function in nlme and the corBrownian and
corMartins functions in ape. But, we are interested in
incorporating the within-species variation in our small
dataset.
Any suggestions would be welcome!
Thanks for your help, Andrea
~~ Andrea Berardi, PhD Postdoctoral Researcher, Smith Lab
EBIO, University of Colorado-Boulder
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--
Simon Blomberg, BSc (Hons), PhD, MAppStat, AStat.
Senior Lecturer and Consultant Statistician
School of Biological Sciences
The University of Queensland
St. Lucia Queensland 4072
Australia
T: +61 7 3365 2506
email: S.Blomberg1_at_uq.edu.au
http://www.evolutionarystatistics.org
Policies:
1. I will NOT analyse your data for you.
2. Your deadline is your problem.
Statistics is the grammar of science - Karl Pearson.
_______________________________________________
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