In discussions like these it would be helpful if the writer could clarify 
whether they are referring to the concepts of biological homology, topological 
homology or "semantic homology". These aren't the same things and the whole 
issue of “homology” in geometric morphometrics has always seemed, at least to 
me, to be very confused. For example, refer to the definitions of “homology” 
and “landmark” in the Glossary on the SB Morphometrics web site. Because it 
means different things to different specialists homology isn't a term to be 
thrown around as lightly as morphometricians seem prone to do. Imprecise and/or 
ambiguous usage renders the meaning of sentences difficult or impossible to 
understand for me and I suspect confuses others as well.

Norm MacLeod


> On 3 Jun 2017, at 08:53, alcardini <alcard...@gmail.com> wrote:
> 
> Hi Philipp,
> I am not worried about the number of variables (although I am not sure
> one needs thousands of highly correlated points on a relatively simple
> structure and seem to remember that Gunz and you suggest to start with
> many and then reduce as appropriate).
> 
> Regardless of whether point homology makes sense, I am worried that
> many users believe that semilandmarks (maybe after sliding according
> to purely mathematical principles) are the same as "traditional
> landmarks" with a clear one-to-one correspondence. Even saying that
> what's "homologous" is the curve or surface is tricky, because at the
> end of the day that curve/surface is discretized using points, shape
> distances are based on those points and there are many ways of placing
> points with no clear "homology" (figure 7 of Oxnard & O'Higgins,
> 2009); indeed, in a ontogenetic study of the cranial vault, for
> instance, where sutures may become invisible in adults and therefore
> cannot be used as a "boundary", semilandmarks close to the sutures may
> end up on different bones in different stages/individuals.
> 
> Semilandmarks are a fantastic tool, which I am happy to use when
> needed, but they have their own limitations, which one should be aware
> of.
> Cheers
> 
> Andrea
> 
> 
> 
> On 03/06/2017, mitte...@univie.ac.at <mitte...@univie.ac.at> wrote:
>> I think a few topics get mixed up here.
>> 
>> Of course, a sample can be too small to be representative (as in Andrea's
>> example), and one should think carefully about the measures to take. It is
>> also clear that an increase in sample size reduces standard errors of
>> statistical estimates, including that of a covariance matrix and its
>> eigenvalues. But, as mentioned by Dean, the standard errors of the
>> eigenvalues are of secondary interest in PCA.
>> 
>> If one has a clear expectation about the signal in the data - and if one
>> does not aim at new discoveries - a few specific measurements may suffice,
>> perhaps even a few distance measurements. But effective exploratory
>> analyses have always been a major strength of geometric morphometrics,
>> enabled by the powerful visualization methods together with the large
>> number of measured variables.
>> 
>> Andrea, I am actually curious what worries you if one "collects between
>> 2700 and 10 400 homologous landmarks from each rib" (whatever the term
>> "homologous" is supposed to mean here)?
>> 
>> Compared to many other disciplines in contemporary biology and biomedicine,
>> 
>> a few thousand variables are not particularly many. Consider, for instance,
>> 
>> 2D and 3D image analysis, FEA, and all the "omics", with millions and
>> billions of variables. In my opinion, the challenge with these "big data"
>> is not statistical power in testing a signal, but finding the signal - the
>> low-dimensional subspace of interest - in the fist place. But this applies
>> to 50 or 100 variables as well, not only to thousands or millions. If no
>> prior expectation about this signal existed (which the mere presence of so
>> many variables usually implies), no hypothesis test should be performed at
>> all. The ignorance of this rule is one of the main reasons why so many GWAS
>> 
>> and voxel-based morphometry studies fail to be replicable.
>> 
>> Best wishes,
>> 
>> Philipp
>> 
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> 
> 
> -- 
> 
> Dr. Andrea Cardini
> Researcher, Dipartimento di Scienze Chimiche e Geologiche, Università
> di Modena e Reggio Emilia, Via Campi, 103 - 41125 Modena - Italy
> tel. 0039 059 2058472
> 
> Adjunct Associate Professor, School of Anatomy, Physiology and Human
> Biology, The University of Western Australia, 35 Stirling Highway,
> Crawley WA 6009, Australia
> 
> E-mail address: alcard...@gmail.com, andrea.card...@unimore.it
> WEBPAGE: https://sites.google.com/site/alcardini/home/main
> 
> FREE Yellow BOOK on Geometric Morphometrics:
> http://www.italian-journal-of-mammalogy.it/public/journals/3/issue_241_complete_100.pdf
> 
> ESTIMATE YOUR GLOBAL FOOTPRINT:
> http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/
> 
> -- 
> MORPHMET may be accessed via its webpage at http://www.morphometrics.org
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_____________________________________________________

Professor Norman MacLeod
The Natural History Museum, Cromwell Road, London, SW7 5BD
(0)207 942-5204 (Office Landline)
(0)785 017-1787 (Mobile)
http://paleonet.org/MacLeod//

Department of Earth Sciences, University College
London, Gower Street, London WC1E 6BT, UK

Nanjing Institute of Geology & Palaeontology,
Chinese Academy of Sciences, 39 Beijing, Donglu, Nanjing, China
_____________________________________________________














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