Dear SPMers,
we have an experiment with 2 groups of subjects (controls/patients) and
3 conditions for each subject. We set the 2nd level analysis using
flexible factorial design option in SPM5.
The main effect of subject, group and condition and interaction of
group/condition were included in design matrix.
The contrast weights for main effect of group was set according to
technical note of Jan Glascher and Darren Gitelman.
The problem is when the main effect of subject is included in design
matrix. This results in widespread activation on 0.05 FWE level with
very high t-values. When the main effect of subject factor is not
included in the design matrix the activation is less extensive (and
probably more credible).
This is in accord with the Darren Gitelman's note of improved
sensitivity of a model where the main effect of subject is included in
the design matrix.
The question:
When the subject effect is included the inter-subject variability
doesn't end up in residuals (or at least not all) which induce higher
t-values. But isn't the inter-subject variability crucial for assesing
of significance of tested effect?
Am I completely wrong? Which design is more resonable then?
Thank you for any comments or notes on this issue.
Radek Marecek
Dep. of Neurology
St. Anne's University Hospital
Masaryk University
Brno, Czech Republic
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