#1
My reasoning is that only #1 will reproduce the results of a
one-sample t-test of the difference of paired images. #1 also matches
the paired t-test in SPM.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Mon, Aug 6, 2012 at 11:56 AM, Gabor Oederland <[log in to unmask]> wrote:
> Thanks for the quick reply!
>
>
> To verify, as there are quite a few possibilities: In case the assumptions of SPM hold, then which specific models for a within-subject model would be correct?
>
> 1) Flexible factorial with factor "subject"
> 2) Flexible factorial without factor "subject"
> 3) Full factorial with factors (independence no, variance equal) according to design of the experiment
> 4) Full factorial similar to 3) with additional factor "subject" (independence yes, variance unequal)
>
> As far as I can see, Full factorial does not directly compare e.g. con image 1 of subject 1 with con image 2 of the same subject, so this approach should be wrong in any case?
|