To better answer such questions, I usually recommend that step 1 in an analysis 
to do an analysis of relative warps (PCA). A real outlier (caused, for example, 
digitizing landmarks out of order on a specimen) should then stick out in the 
scatter plot. If one specimen was reflected then the point will stick way out. 
If the plot just looks like a noisy scatter then you have to ask whether that 
is “real” (that specimen really does have a different shape or could be a small 
problem in digitizing).  

 

----------------------

F. James Rohlf, Distinguishedl Professor Emeritus, Stony Brook University 

The much revised 4th editions of Biometry and Statistical Tables are now 
available:

http://www.whfreeman.com/Catalog/product/biometry-fourthedition-sokal

http://www.whfreeman.com/Catalog/product/statisticaltables-fourthedition-rohlf

Please consider the environment before printing this email

 

From: Zakia [mailto:[email protected]] 
Sent: Wednesday, May 27, 2015 3:23 PM
To: [email protected]
Subject: [MORPHMET] Need help,Outlier analysis in MorphoJ

 

Hi All !

 

I am a novice in geometric morphometrics methods and I need some aid if it 
possible.

 

I study morphology of leaves in one specie and eventually her hybrid. 30 trees 
was selected in two sites and 20 leaves per tree was harvested. the landmarks 
was digitised with tpsDig2 with repetition.

I analysed my data with tpsSmall,  the results show of correlation = 0.999 and 
SM root error = 0.0007.

 

When I analysed data in MorphoJ, after procrust superposition, in “Find 
Outliers” analysis shown on the left, the maximum was 75.32 and the minimum 
6.98. I don’t know what the significance? does that mean there is   error in 
the digitization? or there is high variability? should I remove the great 
values?

 

thanks for your aid

 

C. Zakia

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