On 05/11/2018 18:50, Diego Ardón wrote:

Captura de pantalla 2018-11-05 a la(s) 11.40.26.pngThank you Mr. Fruciano. I had already made the DFA, but wasn't aware thegraphical output represented both groups (it certainly makes sense). Ihave a couple of other questions regarding semi-landmarks. I probablyshould start a new topic, but I'll first try out here:So, I was adviced to use semi-landmarks, I placed them with MakeFan8,saved the files as images and then used TpsDig to place all landmarks,however I didn't make any distinctions between landmarks andsemi-landmarks. What unsettles me is (1) that I've recently comed acrossthe term "sliding semi-landmarks", which leads me to believesemi-landmarks should behave in a particular way.

`Well, it's a long topic, but the general idea is that, to account for`

`the uncertainty in placement of a semilandmark along a curve, this is`

`slid along the curve itself (or, more frequently, its approximation) so`

`that ideally only variation perpendicular to the curve (reflecting the`

`curvature) is retained.`

`In current practice, semilandmarks are slid. Various software can do`

`this, the most popular for 2D data being certainly tpsRelW by F.J. Rohlf.`

A good, recent and accessible treatment of this topic is:

`Gunz & Mitteroecker 2013. Semilandmarks: a method for quantifying curves`

`and surfaces. Hystrix`

The second thing thatunsettles me is whether "more semi-landmarks" means a better analysis.

Not necessarily.

Ican understand that most people wouldn't use 65 landmarks+semilandmarksbecause it's a painstaking job to digitize them, however, in my recentreads I've comed across concepts like a "Variables to specimen ratio",which one paper suggested specimens should be 5 times the number ofvariables. I do have a a data set of nearly 400 specimens, but it doescome short if indeed I should have 65*2*5 specimens!

`There are two issues: 1. whether statistical procedures are defined, 2.`

`whether one has enough power and/or how large is error in estimates.`

`The first issue is easy to deal with: certain statistical procedures`

`(for instance, the ones involving matrix inversion) are not defined if`

`there are many variables and relatively few cases. These procedures`

`simply "don't work". However, there are other alternative procedures`

`which do work (e.g., the ones based on distances) and/or workarounds`

`(e.g., use of generalized inverses).`

`The second issue is much more complex and I doubt one can give a`

`straightforward answer. In general, the more observations (specimens)`

`the better (when one can get them, that is). But the idea of a certain`

`number of observations relative to the number of variables is, at best,`

`a rule of thumb.`

`Clearly, having too many variables can create problems and artifacts. An`

`interesting recent example of this can be found in`

`Bookstein 2016 - A newly noticed formula enforces fundamental limits of`

`geometric morphometric analyses. Evolutionary Biology`

`In your particular case, if I were you I would ask myself whether all`

`those points/semilandmarks are that necessary to capture biologically`

`relevant variation. That is a question that only you can answer, based`

`on your knowledge of the biological problem at hand.`

`Statistical power and reliability of estimates is another issue, which`

`is in part dataset-dependent (as well as dependent on which statistical`

`procedures you intend to use). An interesting paper dealing with this is`

`Cardini 2007. Sample size and sampling error in geometric morphometric`

`studies of size and shape. Zoomorphology`

`In general, as said above, it's very hard to give straightforward`

`answers to your question.`

I hope this still helps, though. Carmelo ================== Carmelo Fruciano Institute of Biology Ecole Normale Superieure - Paris CNRS http://www.fruciano.it/research/

El lunes, 5 de noviembre de 2018, 2:12:20 (UTC-6), Carmelo Frucianoescribió:On 03/11/2018 22:28, Diego Ardón wrote: > Dear Mr. Soda, > > Thank you for replying. Your statement " setting one group’s mean shape > to be the starting shape and the other group’s to the target; this will > lead to the most direct comparison. " pretty much describes what I have > in mind to do. Which software could I use to do this? since I believe > MorphoJ will not do it. Dear Diego, MorphoJ will actually do it. The easiest is to use what is under the menu "Discriminant analysis". MorphoJ's user guide has a brief but very clear description of the graphical output. I hope this helps. Best, Carmelo--================== Carmelo Fruciano Institute of Biology Ecole Normale Superieure - Paris CNRS http://www.fruciano.it/research/ <http://www.fruciano.it/research/> > El miércoles, 31 de octubre de 2018, 13:51:07 (UTC-6), K. James Soda > escribió: > > Dear Mr. Ardón, > > Good question. Whenever we make shape comparisons in GM, be that via > displacement vector or deformation grid (which is what you’re > doing), we can typically only compare two shapes at a time. One > shape is called the reference (or starting shape, in this case). > This is the shape for which the grid would look “normal”; straight, > equally spaced grid lines. The second is the target, where the grid > is deformed to take this second configuration. If you want to > compare two geographic groups, I would suggest setting one group’s > mean shape to be the starting shape and the other group’s to the > target; this will lead to the most direct comparison. I am not > certain how easy this is to do in MorphoJ, though. > > Hope this helps, > > James > > On Oct 31, 2018, at 12:01 PM, Diego Ardón <diegoar...@gmail.com > <javascript:>> wrote: > >> Hello, my name is Diego and I'm currently undertaking a Master's >> program in Mexico. One of my thesis project involves a geometric >> morphometrics study on the shape of a freshwater fish which >> distributes across Central America. I'm currently having trouble >> with a concept that will probably be very simple to most of you, >> but which I haven't found a way to get my head around. >> >> I'm running a CVA on MorphoJ, dividing my dataset into two >> geographically distinct groups. I run the test and change the type >> of graph to a "Warped Outline Drawing". So now the graph is >> showing a "starting shape" which I interpret as it being the >> average of all my landmark data (both geographical groupings), >> however I'm not sure on how to interpret the "target shape". I was >> expecting to have two "target shapes", one for each of the >> geographical groupings. Could someone please help point out my >> misunderstanding and offer me a way on how to interpret the >> "target shape"? >> >> Thank you, I'll be very thankful >> >> Diego Ardón >> >> -- >> MORPHMET may be accessed via its webpage at >> http://www.morphometrics.org >> --- >> You received this message because you are subscribed to the Google >> Groups "MORPHMET" group. >> To unsubscribe from this group and stop receiving emails from it, >> send an email to morphmet+u...@morphometrics.org <javascript:>. > > -- > MORPHMET may be accessed via its webpage at http://www.morphometrics.org > --- > You received this message because you are subscribed to the Google > Groups "MORPHMET" group. > To unsubscribe from this group and stop receiving emails from it, send > an email to morphmet+u...@morphometrics.org <javascript:> > <mailto:morphmet+u...@morphometrics.org <javascript:>>.--================== Carmelo Fruciano Institute of Biology Ecole Normale Superieure - Paris CNRS http://www.fruciano.it/research/ <http://www.fruciano.it/research/> -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org ---You received this message because you are subscribed to the GoogleGroups "MORPHMET" group.To unsubscribe from this group and stop receiving emails from it, sendan email to morphmet+unsubscr...@morphometrics.org<mailto:morphmet+unsubscr...@morphometrics.org>.

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