For the 3x2 ANOVA, the F-contrast should be: [0 0 0 0 0 1 -1 0 -1 1 0;
0 0 0 0 0 0 1 -1 0 -1 1].
The post-hoc tests:
[0 0 0 0 0 1 -1 0 -1 1 0]
[0 0 0 0 0 0 1 -1 0 -1 1]
[0 0 0 0 0 1 0 -1 -1 0 1]
For task differences at a specific time window, I'd really recommend
GLM Flex (partition the variance by each within-subject factor), but
in the case of SPMs GLM:
[0 0 0 1 -1 1 0 0 -1 0 0]
I've written several post on creating contrasts and would suggest that
you search the list archives. Use the term S1G1C1.
** This assumes that the first 3 columns are time windows, the next 2
are task, the next three of time windows of task 1 and the last 3 are
time windows for task 2.
** You should be using the flexible factorial
** You should also have a subject factor in the model, if its not already there.
For viewing purposes, you might also want to create the negative of
the above contrasts, although peak_nii and OrthoView can both pull out
both positive and negative values.
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
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On Wed, Jan 9, 2013 at 10:11 PM, Jun Wang <[log in to unmask]> wrote:
> sorry, could you make it more clear. I am pretty new for this contrast
> stuff. In this 2X3 repeated design, the F contrast should be set as [0 0 0 0
> 0 1 0 -1 -1 0 1] or something else. and what the contrast set if I want to
> know the simple effect about task difference on different time window.
>
> thanks
> Jun
>
>
> On Wed, Jan 9, 2013 at 9:05 PM, MCLAREN, Donald <[log in to unmask]>
> wrote:
>>
>> You'd still need the F-contrast even in that case. Post-hoc tests
>> would be the same as I stated.
>> There are some things in the Glascher document that should be updated.
>> It's been on my list for quite some time, but never at the top of the
>> list.
>>
>> 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 Wed, Jan 9, 2013 at 9:46 PM, Jun Wang <[log in to unmask]> wrote:
>> > Thanks,Donald. If my two factors are all within subject factor(3 time
>> > window
>> > and 2 task condition), then I can use the contrast [0 0 0 0 0 1 0 -1 -1
>> > 0
>> > 1]. right ( I just followed the example from Glascher's paper). in this
>> > case, how should I set the contrast for posthoc t test right. basically,
>> > I
>> > want to know the task difference on different time window
>> >
>> > thanks
>> > Jun
>> >
>> >
>> > On Wed, Jan 9, 2013 at 8:14 PM, MCLAREN, Donald
>> > <[log in to unmask]>
>> > wrote:
>> >>
>> >> On Wed, Jan 9, 2013 at 9:08 PM, Jun Wang <[log in to unmask]> wrote:
>> >> > Dear spm experts,
>> >> > I have a question regarding to post hoc t test in spm. I have a 2X3
>> >> > (group
>> >> > by task ) repeated design and got significant interaction when I used
>> >> > contrast [0 0 0 0 0 1 0 -1 -1 0 1].
>> >>
>> >> >>>> The correct interaction contrast is an F-test. [0 0 0 0 0 1 -1 0
>> >> >>>> -1 0
>> >> >>>> 0; 0 0 0 0 0 0 1 -1 0 -1 1]. This will tell you if there is an
>> >> >>>> interaction
>> >> >>>> between the task effects and group. From this, you could test for
>> >> >>>> pairwise
>> >> >>>> task difference interacting with your groups. With the post-hoc
>> >> >>>> t-test of [0
>> >> >>>> 0 0 0 0 1 0 -1 -1 0 1], you know the direction of the effect and
>> >> >>>> don't need
>> >> >>>> any further tests.
>> >>
>> >>
>> >> Then I want to do post hoc t test to
>> >> > tell the direction of interaction( e.g. group difference on task1).
>> >> > Should I
>> >> > extract ROI activity from significant cluster found in the
>> >> > interaction
>> >> > effect and do the simple t test outside spm or should I set different
>> >> > contrast in same SPM design. if it is the latter case, how should I
>> >> > set
>> >> > the
>> >> > contrast.
>> >>
>> >> >>>> Testing the group effect of a single task in a repeated-measures
>> >> >>>> design is not valid with the standard GLM. You'll need a 2-sample
>> >> >>>> t-test. If
>> >> >>>> you use GLM Flex, then you can test the group effect of individual
>> >> >>>> tasks.
>> >>
>> >> >
>> >> > thanks for your input
>> >> >
>> >> > Jun
>> >
>> >
>
>
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