Hi Doug
The following is just a suggestion, and I hope that tougher SPMers correct
me if its wrong.
If I understood it well what you are looking for, are the areas related
with high or low performance across subject. This suggest a parametric
factorial design. I think that you may simply have to adjust your contrast
properly. Just multiply the desired subtraction (say Lecture vs control) by
the performance of your subjects. Then subtract the mean to have a contrast
sum of 0. I suggest that you use masking and correction for small volume
using this mask (the mask will be the general Lect vs control for example).
I hope that this doesn't sounds too crazy.
Best regards
Jack
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| Jack Foucher Universite Louis Pasteur |
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-----Message d'origine-----
De: [log in to unmask] [SMTP:[log in to unmask]]
Date: mercredi 1 decembre 1999 13:48
A: [log in to unmask]
Objet: evaluating role of covariate
I'm trying to evaluate a possible role of task performance as a covariate
source of activation during various language tasks.
Using a delayed boxcar design, our subjects perform various language tasks
(emphasizing orthographic, phonological, semantic or syntactic processes),
with each task alternating with a control task. We suspect that various
factors (including behavioral performance) may influence the degree of
activation -- and maybe even the location of activation since more advanced
readers tend to activate different brain areas than early readers. How can
I
evaluate the possible role of behavioral performance (% correct) as a
covariate across subjects? More specifically, how can I identify how much
of
the variance can be attributed to this covariate?
Doug Burman
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