I actually has a visual task and a tactile task. In situation 1
(separate one-sample t-test), visual activation for visual task and
tactile activation for tactile task were got. However, stronger visual
activation for visual task or stronger tactile activation for tactile
task was not observed when compare the two task in situation 2 (paired
t-test), just because there are no visual activation for visual task
or no tactile activation for tactile task in situation 2. Even though
there is no problems with spm, how to explain the above results?
Xiang
On Mon, Jun 8, 2009 at 1:10 PM, Dasa
Zeithamova<[log in to unmask]> wrote:
> Perhaps I misread your question, but If I understand it correctly, you are
> doing two VERY different analyses in Situation 1 and Situation 2, so you
> shouldn't be surprised that the results are different.
> In 1, you look which areas are active in cond A, and which are active in B.
> You get areas where A> baseline, and areas where A>baseline. In 2, you are
> essentially performing a t-test looking for areas where A>B (i.e. where
> A-B>0). Neither of A or B has to be above baseline for A>B and both A & B
> can be above baseline and equal.
> Is that what you were after?
>
> Dasa
>
>
> Xiang Wu wrote:
>>
>> Hi all
>>
>> Given two conditions A and B.
>> In situation 1, I perform group analysis one sample t-test on A and B
>> "separately". So I got activations for A and B.
>>
>> In situation 2, I put A and B in "one group analysis". I conduct two
>> sample
>> t-test, paired t-test, or full-factorial (one factor, two level), the
>> results were similar. However, The activations for A and B in "one group
>> analysis" are largely different from those by "separate" one sample
>> t-test,
>> not only the significance level, even the activation patterns look
>> different.
>> I really confused. Can somebody explain the reason for me? I think there
>> is
>> no problem to get activation of each condition with one sample t-test, but
>> I
>> have no idea what happened when put multiple conditions in one group
>> analysis.
>> Thanks Xiang
>>
>
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