Dear Colleagues,
I have a question concerning the test of parameters in a second level
design with two groups. I am using one parameter (lets say
"performance") for each subject:
group Par group1 Par group 2
1 1.2 0
1 3.4 0
1 -2.5 0
1 4.3 0
... ... ...
2 0 3.3
2 0 1.8
2 0 -2.2
2 0 3.6
... ... ...
Both parameters are normalized (mean 0, var 1).
To investigate the *negative* correlation between this parameter and the
contrast images in two groups I've used the contrast vector '-1 0' for
group 1 and '0 -1' for group 2. This revealed a strong *negative*
correlation in group 1, whereas the correlation for group 2 was not
significant (neither negative nor positive).
As a next step I would like to compare both groups. I've used the
contrast '1 -1' which revealed highly significant results. But how can
this be explained?
Does this mean that the general *dependence* between parameter and
contrast value is bigger in group1 than in group2, no matter if it is a
negative or positive correlation?
Or does "1 -1" mean that the *positive* dependence in group1 is bigger
than in group2? If yes, this would not fit with the results found for
the groups separately. Or does this contrast compare the slopes of the
correlation, and just show that the one slope is steeper than the other?
Thanks a lot four your help,
Karsten
(The design matrix was constructed with "Glm" and the statistics was
computed with "randomise".)
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