Hi Lara,



Question 1:

shapeAnalysisMANCOVA allows for including variables that ICV correct any measurements, given that you know total brain volume.
(in the wizard, in the test parameters tab, under the "reinterprets the scaling column values etc...") is where you would click tthis option to have your data ICV corrected. For correcting for age you will have to list them as independent variable. For testing diagnosis and sex, probably you could model them using a set of binary variables similar to what we propose here (http://www.insight-journal.org/browse/pu...)
Examples of commandlines are also provided in the aforementioned paper.



Question 2:

I think it would be safe to report significant shape changes, even if the FDR or Bonferroni (especially with Bonferroni, since it is a much more strict correction test) result into small clusters of significance. I would actually look at how those clusters look in the raw P maps as well.



Question 3:

The differences between DiffMagnitude_original attribute and "DiffMagnitude" (range 0-100) are sadly a result of having no maintenance support for the module. The released and discontinued version of SAM that you are using, generates MRML 3DSlicer scenes for visualization of statistical results of this program in Slicer. Slicer back in the years when we developed this (2010) did not have a good visualization scheme for continuous variables (such as structural differences). Slicer allowed though visualizing color labels (that they had capped at 100) so in order to use that infrastructure we had to rescale our continuous variable maps from 0-100. DiffMagnitude is that scaled map. Your real map and the one you want to report results with is DiffMagnitude_original. Sorry about the confusion. We are working on gathering funding for a new shape statistical package and we will keep you posted, as well as have all these bugs in mind for correction.



I hope that helps!
Thanks,


Beatriz