Sorry, couple more questions:
1) I know that QDEC's/mri_glmfit's equivalent in FSL ("randomise") applies
the GLM by doing permutations, and so already corrects for multiple
comparisons in the process. How similar is this to what Monte-Carlo does
(i.e. controlling FWE via repeated simulations) upon the initially
uncorrected QDEC results?
2) In FSL, a comparison between groups A and B is tested by defining both a
"A>B" as well as a "B>A" contrast - the reason being (as far as I
understand) that taking the logical complement of "A>B", i.e. inverting the
t-values in the statistical map, is *not* equal to the map produced by the
cotnrast "B>A". How come, then, that QDEC phrases the group contrast in a
"two-tailed" way (i.e. "do groups A and B differ")? Is the dichotomy not
necessary in QDEC, or is it simply done behind the scenes?
3) I've read papers where the thickness from *native*-space was used in the
analyses, even though initially T1-weighted images were initially aligned
to the ICBM 152 template. Why isn't thickness from this *standard*-space
used, as happens in FSLVBM with grey matter density? Why even register to
the template in the first place if you're then going to go back and use
native-space values?
Thanks!
On 6 March 2014 10:20, Tudor Popescu <tud...@gmail.com> wrote:
> Thank you very much Doug.
> Tudor
>
>
> On 6 March 2014 03:53, Douglas Greve <gr...@nmr.mgh.harvard.edu> wrote:
>
>>
>> On 3/5/14 5:25 PM, Tudor Popescu wrote:
>>
>> Hello, I have some questions on doing group comparisons with thickness,
>> area and volume. Many thanks in advance for any help!
>>
>> 1) For a DOSS design with group and gender as categorical factors, I see
>> that an interaction contrast ("Is there a group-gender interaction in the
>> mean thickness?") still exists - but what does this contrast mean, given
>> that DOSS by definition doesn't allow for interactions?
>>
>> Are you using QDEC? If so, don't use the DOSS as the contrasts are
>> incorrect. It is possible to have an interaction among the categorical
>> factors with a DOSS.
>>
>>
>> 2) it makes sense that measures such as thickness are analysed
>> vertex-wise in QDEC, however what does it mean when the dependent variable
>> is area or volume - measures that do not make physical sense for a single
>> vertex but only at the level of a region consisting of *several* vertices?
>>
>> The interpretation is a little more difficult. Each vertex is assigned an
>> area equal to the average of the triangles adjacent to it. This is just a
>> value that can be mapped to a common space like any other value (eg,
>> thickness) (but there is a special jacobain correction to account for
>> stretching or compression). Smoothing reduces the effect of having
>> different sized triangles. One can think of it like this: in the common
>> space (fsaverage) image having a patch of a certain size. When you mapped
>> that patch back to each individual, how big would that patch be? You could
>> then do group statistics on that number. In this way you could analyze the
>> entire hemisphere. Now imagine doing this but making the patch smaller and
>> smaller.
>>
>>
>> 3) For values extracted from atlas regions with aparcstats2table, it
>> seems that the product of the extracted CT and area is in the same order of
>> magnitude as the extracted volume, but never really the same or even close
>> - why, when the volume of a region should theoretically be the product of
>> its surface area by its thickness?
>>
>> It is an issue of how it is computed. Sum(CT*Area) != Sum(CT)*Sum(Area).
>> When computing volume, CT*Area is computed for each vertex then summed
>> across vertices.
>> doug
>>
>>
>> Tudor
>>
>>
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