Hi,
If you are doing a higher level analysis then all of your subjects
should be in
the same (standard) space. Hence it doesn't really matter which image
you
use as the background image (which is what example_func is used here
for).
If you look at the two images they should look pretty much the same,
if not then
there may be issues with your registrations to standard space.
All the best,
Mark
On 1 Jul 2009, at 19:52, Sushravya Raghunath wrote:
> Experts,
>
> I have Young (controls and patients) and Old (controls and patients)
> data. I want to carry out conjunction analysis of (Young control >
> Young patients) and (Old controls > Old patients). I have the third
> level feat analysis results for Young and Old run separately with
> contrast control > patients.
>
> I am trying to use easythresh_conj as mentioned in the quoted mail
> below as p.s.
>
> In easythresh_conj stats/zstat1 stats/zstat2 mask 2.3 0.05
> example_func grot, if I use zstat1 of Young and zstat1 of Old then
> what would example_func be? I would have two example_func, one for
> young and one for old.
>
> Can I carry out analysis this way? Any help would be appreciated,
>
> Thanks,
> Sushravya
>
> p.s:
>
> "Dear Yvonne,
> I saw your first message and meant to reply, but Tim & Joe have done
> most of the work. Just to clarify/amplify:
>
> The product of p-values approach only works (as Tim said) to test
> the 'global' null hypothesis (no effects real), not the conjunction
> null (as many as all but one effect real).
>
> Testing the conjunction null works by creating a min z image, and
> making inference on it just as if it were a regular z image. This
> applies to uncorrected voxel-wise and corrected voxel- and cluster-
> wise inferences.
>
> As a stab at this, take a look at the attached easythresh_conj. If
> you supply it two z images, it will do conjunction inference on them
> and give you the standard easythresh output.
>
> easythresh_conj stats/zstat1 stats/zstat2 mask 2.3 0.05 example_func
> grot"
>
> If you look at the code, all it does is take the min of the two z
> images and then do all the other easythresh stuff on the min.
>
> One detail is that easythresh has to estimate the smoothness from
> the statistic image itself, which results in varying P-values for
> the same cluster sizes depending on the z images used. If you have
> a single feat directory from which the images come from, try using
> the -s option to specify the smoothness file (stats/smoothness),
> which will give more accurate (and contrast-independent) P-values.
> E.g.
>
> easythresh_conj -s stats/smoothness stats/zstat1 stats/zstat2 mask
> 2.3 0.05 example_func grot"
>
> Lastly, note that this is a conservative procedure... i.e. proper
> conjunction inference has to account for the worst case scenario,
> where one statistic image is wildly significant, and the other one
> null. Because of this, you may find it hard to attain significance
> with this method. Just a warning.
>
> Let me know if you have any troubles with it.
>
> -Tom"
>
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