Jack wrote:
>I would recommend two regressors in the design matrix
>a) onset, RT_t,1
>b) onset, RT_t, RT_m
>where RT_t is the trial RT and RT_m is the mean RT for the experimental condition of the trial. I would not orthogonalize.
>> (cA-iA)- (cB-iB) = 1 -1 -1 1
>Your contrast of interest for this design matrix is [0 1]. That is, the (cA-iA)-(cB-iB) contrast is implicit in the second regressor, so you >won't need to do a 1 -1 -1 1 or 1 -1 contrast and also no need to add RT to the second level analysis.
Hi Jack,
thanks for your feedback, but I cannot completely understand it.
I thought to have learnt that the second regressor (those having a phenomena-related 3rd column value) had to be orthogonalized wrt its correspondent EV with fixed value=1. reading more carefully previous posts, I read one reporting that if you fill in the 3rd column with demeaned data you may-not/shouldn't orthogonalize the 2 EV. is it correct??? was it this your proposal??
moreover, I cannot understand how the (cA-iA)-(cB-iB) contrast could be implicit in the second regressor.
according to your design matrix suggestion, i would have 2 EV for each (4) experimental condition.
so i expected to apply this contrast 0 1 0 -1 0 -1 0 1.
considering that each second EV should contain the bold signal changes related to the performance.
where am i wrong???
thanks in advance
cheers,
Alberto
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