Dear Karl and others,
I have hopefully just one more quick follow-up to this discussion. It's
about the differences between specifying the kind of F-contrast we
discussed earlier with regards to Volterra analysis:
A B A*A A*B B*B
> > 1 0 1 0 0 to see which voxels respond to A, and
> > 0 1 0 0 1 to see which voxels respond to B,
... and the alternative kind of F-test,
1 0 0 0 0
0 0 1 0 0 To test the effects of A, and a similar set of 2 contrasts
for B.
The first one should test the average of the betas for the linear and
squared term of condition A, and the second should test whether the linear
and squared terms together model a significant amount of variance
(right?). Would one generally be considered more appropriate in a
Volterra analysis than the other?
Also, if I want to test the DIFFERENCE between A and B, I have to specify
a different kind of contrast, if I can indeed do it with an F-test at
all... I think it would look something like
1 -1 0 0 0 ...for A vs B, linear terms
0 0 1 0 -1 ...for A vs B, quadratic terms
OR
1 -1 1 0 -1 ...to test the averages of linear & quadratic A vs lin. &
quad. B.
Is this a valid way to test for a difference between A and B, in this
case?
Also, it seems that using the second type could take two different forms,
depending on whether I expected the betas for the linear and quadratic
effects to be the same or opposite in sign. It could look like:
1 -1 -1 0 1.
If I expect a "saturation" effect in the haemodynamic response, that
doesn't mean the quadratic betas will be negative, does it? How would a
"saturation" effect be reflected in the betas of the linear and quadratic
regressors?
Thanks very much for your help!
Tor
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