FYI: This is the email I sent to Iman, to which he refers.
----- Original Message ----- From: "niall rooney" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Tuesday, October 17, 2006 1:13 AM Subject: Procrustes Analysis > Hi Iman, > > In reading the various responses to your posting about geometric > morphometric analysis of cleft palates, I notice that your question - > at least as I understood it - wasnt actually addressed directly. You > asked whether both groups should be included in the same analysis or > whether both should be analyzed separately, their results then compared > subsequently? > > I actually posted a similar question with specific regard to Procrustes > Analysis. I was comparing 3-D landmark configurations of human > structures between ethnic and gender groups, and I was advised that the > landmarks of all subjects be included simultaneously in the analysis. > Principal components analysis (PCA) can be applied to the aligned > landmark output of Generalized Procrustes Analysis (GPA), group > differences in the resulting principal component scores serving as a > useful basis for quantifying and interpreting in physical terms the > differences between groups. > > I would suggest the above method. While I used a colleagues software, > which is not publicly available, I could recommend Morphologika, co- > developed by Paul O' Higgins. Check it out. If you choose a set of > landmarks for each subject, you can use this software to carry out GPA > followed by PCA followed by visualization of the differences. > > I should say that I dont know anything about Thin Plate Sline (TPS) > analysis/ warp analysis (this is the alternative, I think, to > superimposition analysis such as Procrustes analysis). While I believe > that that form of analysis is more suited to observing change rather > than difference (e.g. modes of growth from one shape to another over > time), it may also be a method worth investigating. So its maybe worth > asking others. > > Hope this helps. Please find below my verbose query posted to Morphmet > group! > > Best regards, > Niall > > > Niall Rooney > PhD Research Student > Bioengineering Research Centre > School of Electrical, Electronic & Mechanical Engineering > University College Dublin > > > ------------------------------------------------------------------------ > -- > > > > > > > > > >Hello all, > > > >I was hoping someone could give me guidance as to the correct course > of > >action, > >when using GPA followed by PCA to describe difference in form > >between 2 subgroups. Any assistance would be greatly appreciated! > > > >I have a dataset of 200 surface 3-D bone models, from which I have > taken > >seventeen representative 3-D landmarks. The dataset contains Asian/ > >Caucasian, Female/ Male, and healthy/ osteo-arthritic specimens. I > wish to > >describe the differences in form caused by these factors. > > > >I have decided to analyse them in the following way. I have registered > all 200 > >specimens simultaneously, using GPA. I have outputted the > corresponding PC > >scores for PC1-PC6 (90% of variance) for each specimen. I have > calculated the > >average PC scores for each subgroup described above, for PC1-PC6. I > have used > >ANOVA on the PC-scores to identify which PCs (if any) distinguish > >significantly between subgroups. > >Alternatively, I could register all (say) Caucasians with one GPA, then > >register all Asians with a separate GPA, arriving at the mean > configuration > >for > >each group. Procrustes Analysis, followed by PCA could then be applied > >to these 2 mean forms, in order to describe the modes of variation > between > >them. ANOVA obviously could not be carried out on the output in this > >instance, given PC scores for just 2 specimens. Any difference > described by > >PCs > >could not be verified statistically, using this method, I dont think? > >Which of these 2 approaches would you recommend for describing form > >difference, in terms of its PCs? > > > >Additionally, in an effort to generate a surface 3-D model > representing each > >subgroup for further analysis (eg. average Asian and average > Caucasian), the > >surface model of the most normal bone was identified (ie. the specimen > whose > >configuration is closest to the GPA mean configuration/ specimen whose > PC > >scores are closest to zero), then this model was warped to the average > >PC1-PC6 scores for each subgroup. I am able to write out these average > >surface models for each subgroup, along with their corresponding mean > >landmark configuration. For this analysis, I have decided that, for > >instance, the Asian and Caucasian average models should be generated by > >using the same base model (be it Asian or Caucasian) and warping it to > the > >respective PC means of each ethnic subgroup. The alternative option is > to > >model the average Asian using a close-to-normal Asian base model and to > >model the average Caucasian using a close-to-normal Caucasian base > model. > >Although each mean model thus generated would be true to its origins > as it > >were, I fear that to do it this way would be to introduce the > difference > >between the 2 base models, additional to the essential difference in > ethnic > >subgroups, as described by the difference in PC-score averages. Which > of > >these 2 approaches would you recommend? > > > >Many many thanks! > > > >Niall Rooney > > -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
