Dear SPMers,
I have 10 subjects and 4 different conditions. First level stats give me one
contrast image per subject per condition. My question arises with the
second-level statistical analysis. I want to find the effect of each
condition on my group of subjects.
I first performed four different one-sample t-test to test each condition on
my group of subjects. This worked fine, however I thought that it would be
better to use a one-way ANOVA (flexible factorial) in order to take into
consideration the effect of each subject.
To this aim, I used the "flexible factorial" design with two factors :
subject and condition and two main effects subject and condition. To isolate
the effect of one condition I used the following T-contrasts :
Condition 1 : [ones(1,10)/10 1 0 0 0]
Condition 2 : [ones(1,10)/10 0 1 0 0]
Condition 3 : [ones(1,10)/10 0 0 1 0]
Condition 4 : [ones(1,10)/10 0 0 0 1]
The ANOVA leads to much more voxels activated with a FWE-corrected threshold
than the solution using 4 different one-sample t-test. I wonder if that can
be explained by the fact that subjects variability have been identified in
the model ?
Furthermore, I wonder if this approach is right on a statistical point of
view ? I searched the mailing list and only found examples in which one-way
within-subject ANOVA was used for conjunction analysis or difference
between-conditions.
Any thought on this would be highly appreciated,
Camille
|