[Taxacom] Methodological plurality [was cladistic analysis for morphological characters -- UPGMA is not cladistics]

Kipling (Kip) Will kipwill at berkeley.edu
Sat Nov 17 11:27:19 CST 2012

On 11/15/2012 7:51 AM, Ashley Nicholas wrote:
> I guess they do this to assess if there is any congruence in the results of all three analytical methods?

On 11/17/2012 6:42 AM, Dan Lahr wrote:
> More interestingly though, you raise an issue that has always bothered me:
>people using multiple reconstructions methods.  I'll start by saying I do
>not have a strong stance nor the answers to this question.
> In principle, it seems philosophically incoherent

This is a point that triggers my peeve response. The incoherence Dan 
refers to being the root of my discomfort. Different methods have 
unique, but partially overlapping, ontological and epistemological 
starting points and so their congruence cannot be considered to mean 
much of anything at all. And yet, many (most?) publications throw the 
"big three" (ML, Pars, Bayes) at every data set, almost never explaining 
why or what it means, usually then one is picked (with little 
explanation why that one) and the rest ignored. I have facetiously 
suggested to people that if they add UPGMA and NJ that they might feel 
even more warm and fuzzy (or Poy, traditional Hennigian, SWAG, etc.), 
given agreement of 5-7 different methods. Good feeling is the same as 
statistical support, right?

Congruence or conflict across methods tells us little or nothing about 
clade support.

1. These are not independent data being run using the different methods 
so this fails to be support through consilience. If two people that view 
the same world (the data) differently, come to the same result they 
could just as well both be wrong or both be right. That agreement (or 
lack) tells us little about the result, perhaps more about the methods. 
Using Pars for morphology and, for example, ML for DNA sequence data, 
may be a situation where one can invoke consilience, but I doubt that is 
to be preferred over a combined analysis.

2. If one cast all methods to be a form of one particular method (e.g. 
parsimony is just one model of likelihood) and thinks of using the 
different methods as a "sensitivity" analysis, then it is a very poor 
sensitivity analysis indeed. We have many much better ways to explore 
sensitivity of results across parameter space.

3. If congruence is thought of as a measure of support, even as a vague, 
number-free tingly feeling, and if we want to maximize that congruence, 
then this is maximized where all methods converge, which would probably 
can be achieved by using model parameters in ML, etc, to fit parsimony. 
Of course that would be a silly thing to do, unless you really believe 
congruence across methods means something. I don't see statisticians 
using multiple different tests and then implying or claiming that since 
those three test all (or say 2 out of 3) had significant p=values the 
result is "more significant" (increased "truthiness"?).

It is legitimate to do a comparison of methods for its own sake, they 
each have properties worth exploring, but that is rarely what is 
published. One may wish to specifically test certain assumptions, again 
that is valid, but when there is no explanation for the methodological 
plurality, or a simple statement that implies support, e.g. "ML and Pars 
gave basically the save topology" and nothing more, it seems a waste of 
time. If its phylogeny, topology or evolution along branches one is 
after, then pick the appropriate method, justify it and understand its 

Echoing this-

On 11/17/2012 6:42 AM, Dan Lahr wrote:
> you should choose a strategy and stick with it, many of the different analytical methods are logically incompatible.

yep, Dan is right.


Contact info:

Kipling W. Will
Associate Professor/Insect Systematist
Associate Director,Essig Museum of Entomology

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