Hi Hadas,

Thank you for the reply. The test has been conducted previously before 
finalising the landmark points for other users. I suspect the raw bone data 
itself is unsatisfactory. The .obj files generated from 
PACS>MITK>MeshLab>IDAVLandmark to have problems. 

Kind regards,
Helmi

On Tuesday, October 11, 2016 at 4:50:12 AM UTC+8, Hadas L. wrote:
>
> Hi,
>
> I would consider doing a short reliability test on five specimens for each 
> individual for the single point landmarks and the curves. This shouldn't 
> take long and will give you an idea as to whether the landmarks are 
> reliable or not. Ideally this should be done before adding the landmarks to 
> the data set.
>
> Sincerely,
> Hadas
>
> On Sun, Oct 9, 2016 at 5:56 AM, Helmi Hadi <[email protected] 
> <javascript:>> wrote:
>
>> Dear Morphometricians, 
>>
>> I have a weird problem and I was hoping someone could help me on this. 
>>
>> I have the same CT bone (n=400) with 14 landmarks (2 Single point and 12 
>> sliding) larndmarked in IDAV Landmark by three different individuals 
>> following a figure key table. Each individual landmarked 100+ different 
>> bones. The figure key table has the shape of the bone, with the landmark 
>> locations and the order of landmarking. All users were briefed by a single 
>> person (user1) on how to extract the bone and landmark. All three 
>> individuals were present throughout the entire procedure but the bone 
>> segmentation and landmarking process was conducted individually. 
>>
>> When I combine all the data, I noticed that PC1 and PC2 graph has two 
>> clusters. The effect is about 55% (as detailed in the eigenvalues below) 
>> After further checking the classifiers in MorphoJ, the source of the 
>> clustering is one person (user1) landmarked it is slightly differently 
>> compared to the other two. I have checked the outliers tab and no glaring 
>> outliers exists. As the sample size is big, the curve seem to be quite 
>> normal. 
>>
>> Eigenvalues          % Variance     Cumulative %
>>   1.     0.01603351      55.674       55.674
>>   2.     0.00496222      17.230       72.904
>>   3.     0.00224594       7.799       80.703
>>   4.     0.00121085       4.204       84.907
>>   5.     0.00076858       2.669       87.576
>> ...
>>
>> How to interpret the results for this kind of data? Things which come to 
>> my mind are:
>>
>> 1. Maybe the bones for user1 are different compared to the other two 
>> users.
>> Or 
>> 2. User1 thinks the landmark location slightly different compared to 
>> others.
>> Or
>> 3. User2 and 3 could not locate the landmark locations of user1.
>> Or
>> 4. The landmarks selected are unreliable.
>>
>> Ideally I would need few other people relandmark the entire set, but it 
>> is not possible to do it now. Can anyone help shed some light on what is 
>> the probable cause? Thank you.
>>
>>
>> Kind regards,
>>
>> Helmi Hadi, PhD
>>  School of Health Sciences, Universiti Sains Malaysia,
>> 16150 Kubang Kerian, Kelantan, MALAYSIA
>>
>>
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