Hello all.

I am looking for an explanation on what values are actually in an extracted VOI for a Full Factorial Analysis with the levels of one factor not being independent.  I have read the spm_regions.m code and I am not sure I follow it.

The analysis is as follows.

3 groups, 2 time points for each subject.  Mixed-model.

Therefore I set one factor as ‘group’ with 3 levels.  Set independence to yes and variance to equal.

The second factor as ‘time’ with 2 levels.  Set independence to no and variance to equal.

The non-independence in the second factor is what I am having trouble wrapping my mind around.  I know this introduces a non-sphericity correction.  However, If I extract VOI data, I am not sure how the data is being corrected.  I am sure it is, but I am not sure how, or what that exactly means.  i.e.  The xY.y data is not the original values from the subject images, but some type of corrected value.  However, I am fairly certain that if there was no non-sphericity correction, the data extracted would be the original data.

Also, I am also curious as to how SPM5 handles non-independence.  For example, if I have a group at two time points, I can declare non-independence without the groups being equal.  So there does not have to be a matching of subjects like a paired t-test.  So how is this being handled?

I hope I am explaining my questions clearly.  Any help anyone can offer would be fantastic.

Thanks.

-John West

IU School of Medicine