Re:Combining geometric and traditional morphometric datasets

[morphmet_moderator]

----- Forwarded message from morphmet_modera...@morphometrics.org -----

Date: Wed, 05 Feb 2014 22:38:11 -0800
From: morphmet_modera...@morphometrics.org
Reply-To: morphmet_modera...@morphometrics.org
Subject: Re:Combining geometric and traditional morphometric datasets
To: morphmet@morphometrics.org

----- Forwarded message from Soledad Esteban <soledad.este...@icp.cat> -----

Date: Mon, 3 Feb 2014 04:41:41 -0500
From: Soledad Esteban <soledad.este...@icp.cat>
Reply-To: Soledad Esteban <soledad.este...@icp.cat>
Subject: Re:Combining geometric and traditional morphometric datasets
To: morphmet@morphometrics.org

Dear Kara,

You can use different types of variables in each dataset, as far as the variables within each dataset are in a similar scale or range. If you have variables in your linear measurements block with different scales you should standardize them. On the other hand do not think about considering the x and y values as independent variables, they are not, and when working with geometric morphometrics you should consider all the x and y coordinates at the same time.

Hope this helps!

Best wishes

Sole

Soledad De Esteban Trivigno
Area de Paleobiología
Institut Català de Paleontologia
Edifici ICP, Campus de la UAB
08193 Cerdanyola del Vallès
Barcelona. Spain
www.icp.cat

-----Mensaje Original-----
Asunto: Combining geometric and traditional morphometric datasets
De: morphmet_modera...@morphometrics.org
A: morphmet@morphometrics.org
Fecha: 02/01/14 05:28:58

----- Forwarded message from Kara Feilich <kfeil...@fas.harvard.edu> -----

Date: Fri, 17 Jan 2014 16:22:49 -0500
From: Kara Feilich <kfeil...@fas.harvard.edu>
Reply-To: Kara Feilich <kfeil...@fas.harvard.edu>
Subject: Combining geometric and traditional morphometric datasets
To: morphmet@morphometrics.org

Hi all,

I'm fairly new at this, so I hope this question makes sense:
I'm trying to look for covariation and/or modularity among four datasets (all taken from the same individuals, with a phylogeny), where one dataset has Procrustes coordinates for body landmarks, and the other datasets use linear measures. Is there a way to look for (even just two-way) covariation among the datasets? I would like to use a partial least squares approach, but I'm not sure if the single dimension linear measures will play with the two dimensional landmarks.

Though, if the landmark coordinates are broken down so that the x and y components of the coordinates are considered independent (i.e. if you have 10 landmarks, it's considered 20 variables), I should be able to just append linear measures as long as I consider them a separate partition, maybe? I hope?

Any ideas on how to work with geometric and traditional measures in tandem would be greatly appreciated.

Thanks,

Kara
_______
Kara Feilich

Lauder Laboratory
Harvard University Museum of Comparative Zoology
kfeil...@fas.harvard.edu
 

 

----- End forwarded message -----

Soledad De Esteban Trivigno
Area de Paleobiología
Institut Català de Paleontologia
Edifici ICP, Campus de la UAB
08193 Cerdanyola del Vallès
Barcelona. Spain
00-34-935868334
www.icp.cat

----- End forwarded message -----

----- End forwarded message -----