 |
 |
Dear FSL experts, I am reposting this question with the hope of making it more clear this time. We have 130 subjects in 4 groups (3 patient groups X,Y,Z and a control group) and we compared the GM volumes between these groups in an ANOVA design. We were asked by a reviewer to do a 'multiple regression with a group variable (e.g. X=4, Y=3, Z=2, Controls=1)' and, 'an independent estimation of group variables' to examine the continuum of GM abnormalities in this sample.I am copying the exact words of the reviewer to give a better idea about what is asked from us (I just changed the group names): " the examination of a potential continuum of abnormalities between these groups is likely the more adequate approach. Given the limited statistical power of this study this is probably best examined in the context of a multiple regression model with a group variable (e.g., Group X = 4, Group Y = 3, Group Z = 2, healthy volunteers = 1) and an independent estimation of (potentially unequal) group variances. Given the strong a priori evidence for a continuous increase in gray matter deficits in prefrontal and temporal cortices over groups, one-sided testing of such a model appears legitimate."
How should the design matrix be to test this? Thank you very much Cagri Yuksel
Hi Cagri,alternatively, you can simply do:fslmaths GM_mod_merg -s 5.1 GM_mod_merg_fwhm12and then run randomise on GM_mod_merg_fwhm12 ...A larger kernel size means that you'd pick up differences that are larger between your two groups. Unless you had possibly two small peaks that merged into a big one by changing the kernel size, if this was not "there" at 7mm, there's a good chance it won't "appear" at 12mm, but it's always better to please the reviewer and just do it :-)Cheers,Gwenaelle--------------------------------------------------------------------Gwenaëlle Douaud, PhDFMRIB Centre, University of Oxford
John Radcliffe Hospital, Headington OX3 9DU Oxford UKTel: +44 (0) 1865 222 523 Fax: +44 (0) 1865 222 717--------------------------------------------------------------------
De : Cagri Yuksel <[log in to unmask]>
À : [log in to unmask]
Envoyé le : Dimanche 8 Janvier 2012 16h34
Objet : Re: [FSL] Kernel size (VBM)
Thank you very much Anderson, just started FSLVBM_3_proc with sigma 5, hopefully it'll work.
Well, in our study we compared 3 groups and we couldnt find difference between two. The reviewer suggests that the small Kernels are better for subcortical structures and larger kernels for cortex (which is actually in contrast to what I had read in a recent review paper). So he recommends using a larger Kernel to reveal the possible cortical GM differences between those 2 groups, which we couldnt find with 7 mm.
Best regards
Cagri
On Sat, 7 Jan 2012 21:18:03 +0000, Anderson Winkler <[log in to unmask]> wrote:
>Hi Cagri,
>
>This can be changed. Perhaps the easiest is if you open the file
>${FSLDIR}/bin/fslvbm_3_proc and change the line 103 (for FSL 4.1.9),
>adding or removing sigmas you want:
>
>* for j in 2 3 4 ; do*
>
>If you want, for instance, sigmas = 5 and 8 mm, just add:
>
>* for j in 2 3 4 5 8 ; do*
>
>Then run again the pipeline from this script onwards.
>
>I wonder, though, what would be the rationale for the reviewer's
>request, as we often wish to have less smoothing...
>
>Hope it helps!
>
>All the best,
>
>Anderson
>
>
>
>On 07/01/12 16:01, Cagri Yuksel wrote:
>> Dear FSLers,
>>
>> We were asked by a reviewer to repeat our VBM study with a FWHM kernel size of 12 mm (we reported results in sigma 3mmx2.3=7 mm). However as far as I know from the FSL-VBM website the highest kernel size FSL allows for VBM analysis is 9 mm (sigma 4x2.3).
>> Is there a way of doing the VBM analysis with FWHM 12 mm kernel ?
>>
>> Thank you,
>>
>> Cagri Yuksel
>>
>>
>
>