Hi Manish,
Hopefully someone with more stats knowledge has replied off
list-already, but if not, I'll try to point you in the right direction
as well as I can.
I think you should be able to get all the variances you're interested
in using contrasts, and with the formula
var(c'*beta) = s^2*c'*pinv(X'*X)*c
for some contrast c of the parameters beta. Where s^2 is the estimated
variance or residual mean square, which I believe is what SPM stores
in the file ResMS.img under your results directory.
So if you define suitable contrasts for the subject and/or task
regressors in your design matrix X then you should be able to recover
your desired variances. It won't matter what order of A and I you
have, so long as the design matrix correctly codes this.
I hope this helps (and isn't wrong!), and to be honest, I hope someone
else replies with a better answer...
Best,
Ged.
Manish Dalwani wrote:
> Hi SPM'ers,
>
> I have a conceptual question and would be grateful if someone could help
> me understand it. Let's say I have rapid event task where I have 2
> conditions Active and Inactive. I, originally, had the task designed as
> Active Inactive Active Inactive....
>
> But have decided to add jitter and pseudorandomize the trials....so it
> could be A I A A I A I I .....for optimization to get better estimation
> efficiency (Dale, 1999).
>
> Now as I understand SPM2 uses a GLM model Y = X B + E
>
> For my experiment it would y = x1b1 + x2b2 + e.
>
> How can I calculate the intrasubject covariance using SPM2? (I think it
> is equivalent to inverse of (XtVX) where V is the correlation matrix).
> Also, lets say I change my design back to A I A I A I.... how can I
> then measure the inter-trial (A-I) variance for the associated pairs? is
> that possible?
>
>
> Thanks,
> Manish Dalwani
> PRA
> Dept. of Psychiatry
> UCHSC
>
>
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