Hi all,
it seems that a lot of people often have problems during the estimation of
2nd level statistics with SPM5. Sometimes estimation is just not possible:
A warning popup appears:
"Please check your data
There are no significant voxels
The globals are plotted for diagnosis"
and then a crash:
Error running job:
Error using ==> plot
Vectors must be the same lengths.
There are a lot of unanswered emails regarding this problem in this SPM
mailbase.
I tried to find a workaround:
After setting up the model for the 2nd level statistic in SPM5 the
corresponding SPM.mat does not contain the non-sphericity matrix SPM.xVi.V,
but it contains an array of non-sphericity components:
SPM.xVi.Vi = {speye(nScan,nScan)}
Setting up the same model in SPM2 yields to a structure with the
non-sphericity matrix SPM.xVi.V, but without SPM.xVi.Vi:
SPM.xVi.V = speye(nScan,nScan)
Now I modified the SPM.xVi for SPM5 in the same way.
This can be done e.g. by inserting
if ~isfield(xVi,'V'),
Vi = struct( 'form','i.i.d.','V',speye(nScan,nScan));
end;
after line 407 in spm_spm.m.
This results in omitting the temporal non-sphericity estimation (behaviour
like in SPM2). Can anyone tell me if this workaround is feasible? Or is the
temporal non-sphericity estimation necessary? Maybe somebody has other ideas
for a workaround...
I have another question. Sometimes 2nd level statistic estimation with SPM5
is possible. But I cannot say in which configuration. Sometimes a simple
t-test works, sometimes not. When estimation is possible, the estimation
procedure ist done twice with temporal non-sphericity estimation in between
(the routine spm_spm.m is called twice!). Does anybody know why this is done
twice and whether this is intended/necessary???
Regards
Sabine
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