Hi Xiaoyu,
again (see also other email) you should not run left hemispheres on the
right. This could introduce a processing bias, especially when you
force all left to be healthy and right to be diseased (or vice-versa).
Instead run your images normally and then for the univariate , simply
compute the diff between the left and right ROI's (always healthy -
diseased). Then do a normal GLM analysis on this signed difference.
Best, Martin
On Tue, 2018-08-28 at 21:27 +, Wang, Xiaoyu wrote:
> External Email - Use Caution
> Hello Freesurfer Developers,
>
> I’m attempting to use Univariate LME analysis to compare the
> symptomatic and asymptomatic hemispheres of early stage Parkinson’s
> disease patients.
>
> I re-organized the data so that the symptomatic hemisphere is the
> left hemisphere and the Asymptomatic is the right (by flipping the
> orig.mgz before recon-all).
>
> I followed the LME model tutorial for univariate on the freesurfer
> wiki and created my qdec.tabel.dat to have the same layout as in the
> example with group 1 as left hemisphere and group 2 as right
> hemisphere.
>
> I have a design matrix to do a simple linear model containing a group
> by time interaction with the contrast of [0 0 0 1 0 0]
>
> After running the F-test however, I noticed that the p-value was
> really inconsistent across atlases.
> I used multiple atlases and noticed that the p-value can be as low as
> 1.00E-30 for many structures.
> This is too good to be true especially since after sending the
> thickness value to a statistician she came back with values greatly
> different from mine.
> However, the Bhat values were similar.
>
> Can someone give me a hint as to what is going on?
>
> Xiaoyu
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