Will Penny wrote:
> Dear Darren,
>
> d gitelman wrote:
>> Hi Matt/Will/SPM
>>
>> I've been reading over this thread. I have a couple questions and I
>> also run
>> into trouble specifying appropriate contrasts.
>>
>> My experiment has 21 subjects in 2 groups- 9 in group 1, and 12 in
>> group 2.
>> Each subject performs 3 levels of a task which is an n-back working
>> memory
>> task.
>>
>> Following the discussion I should have 3 factors (i think)
>> Independence Variance
>> Subject Yes Equal?
>> Group Yes Unequal
>> Condition No* Unequal
>>
>> I would think that condition should be non-independent because they
>> all are
>> drawn from the same subject, but in Will's original email on this
>> topic he
>> chose independent, which I don't understand.
>>
>> Would the variance setup be correct?
>>
>> ------
>> I then chose 1 main effect of subject and 1 interaction of factors 2
>> and 3.
>>
>> this produces a design matrix (attached) with 21 subject columns, then 3
>> columns of the interaction of group 1 with each condition and 3
>> columns with
>> the interaction of group 2 with each condition.
>> ------
>>
>> I can examine some t-tests on the interaction columns. For example this
>> contrast is valid (looking at group differences of condition differences)
>> zeros(1,21) 1 0 -1 -1 0 1
>>
>> but this contrast is not valid (looking at group differences of single
>> conditions)
>> zeros(1,21) 1 0 0 -1 0 0
>>
>
> If you think about this contrast in the following way I hope you can see
> why it is invalid. Consider first, just the part of your design matrix
> for the first 9 subjects (ie. the first group). This contains the 9
> subject effects and the 3 condition effects. Now, if you try doing
> a [1 0 0] contrast here, this will be invalid; we can only use contrasts
> that look for differences among the conditions (you know this from your
> later reply to Matt :-)). The same consideration goes for the second
> part of the design matrix; you can't do a [-1 0 0]. Therefore its not
> surprising you can't do [1 0 0 -1 0 0] for the whole design matrix.
>
> This logic also means you can't test for eg. a main effect of group !!
>
> Which is of course a main reason for setting up the design in the first
> place.
>
> So, my advice is as follows. Don't use designs that mix (i)
> within-subject effects (ie. condition) with (ii) between subject effects
> (group).
>
> Within-subject designs with just 1 factor (eg. 'condition') are fine.
>
> You can test for between group differences in working memory as follows.
> Take two levels of working memory eg. condition 3 minus condition 1.
> Make this contrast for each subject at the first level. Then use these
> differential contrasts in a two sample t-test at the second level (where
> the two samples are the two groups).
>
Thinking further on this, if you were to also create the within subject
contrast cond2 minus cond 1, for each subject at the first level, then
you could enter the 2 contrasts per subject into a second level
analysis. You would'nt then need the subject effects at the 2nd level as
you have used
differential contrasts at the first level. So, you could have a 2x2
design at the second level with 1 factor group, and the other factor
(differential) condition. (Again I stress you don't have the subject
effects at 2nd level). This should work. (So the key is to use
differential contrasts at the first level and don't have subject effects
at the second).
Best,
Will.
> Am cc'ing Karl on this one as I don't want to mislead anyone.
>
> Happy New Year,
>
> Will.
>
> PS. 'repl' is now obsolete.
>
>> ------
>> For the main effect of condition I did an F test
>> [ zeros(1,21) 1 -1 0 1 -1 0
>> zeros(1,21) 0 1 -1 0 1 -1]
>>
>> Is this correct? It seems to be valid.
>>
>> ------
>>
>> I cannot seem to specify a valid contrast for the main effect of group.
>>
>> t-test: ones(1,9) -1*ones(1,12) <- invalid
>> f-test: ones(1,9) -1*ones(1,12) <- invalid
>> f-test: zeros(1,21) 1 1 1 -1 -1 -1 <- invalid
>>
>> and also invalid is the following.
>> f-test: zeros(1,21) 1 0 0 -1 0 0
>> zeros(1,21) 0 1 0 0 -1 0
>> zeros(1,21) 0 0 1 0 0 -1
>>
>> any suggestions or comments? I have attached the design matrix.
>>
>> Darren
>>
>> ----------
>> Darren Gitelman, MD
>> Department of Neurology
>> Northwestern University
>> voice: (312) 908-8614
>> fax: (312) 908-5073
>> page: (312) 695-1849
>> email: [log in to unmask]
>> ----------
>>> -----Original Message-----
>>> From: SPM (Statistical Parametric Mapping)
>>> [mailto:[log in to unmask]] On Behalf Of Matt Shane
>>> Sent: Thursday, December 20, 2007 2:44 PM
>>> To: [log in to unmask]
>>> Subject: Re: [SPM] questions on perfroming 2 x 2 within-subjects
>>> ANOVA in SPM5
>>>
>>> Dear Will (or anyone else who can help),
>>>
>>> Your reply to Michiru was very timely for me, and I have just
>>> attempted to undertake an analysis guided by your steps below. I feel
>>> like the design matrix is correct, but unfortunately the contrast
>>> manager doesn't appear to be appreciating the design I've created.
>>> And so I'm thinking that I might have gone astray from your advice in
>>> some manner.
>>>
>>> In short: I have 30 participants in a 3 (Group) x 3 (TrialType)
>>> mixed-model design. I've thus created 3 factors in the
>>> flexible-factorial model: Subject, Group and TrialType. The design
>>> matrix (which I'm attaching to this post) appears (to me) to be
>>> right: I have 30 subject columns, followed by the three group
>>> columns, followed by the three trial-type columns, and finally the
>>> group x trial type interactions.
>>>
>>> My problem arises when I try to create contrasts in the contrast
>>> manager, however: I'm able to create contrasts with the first 30
>>> 'subject' columns, but I'm told that any contrast utilizing the
>>> 'group' or 'trial type' columns is invalid. Which, obviously, is
>>> problematic since it's the group and trial type that I want to
>>> interrogate!
>>>
>>> Does anyone have any advice? Have I set up my matrix incorrectly? I'm
>>> attaching both the matrix and the .mat file, and would be ever
>>> thankful for anyone willing to take the time to look it over.
>>>
>>> Thanks,
>>> Matt
>>>
>>> __________________________
>>> Matthew S. Shane, Ph.D.
>>> Research Scientist
>>> The MIND Institute
>>> 1101 Yale Blvd NE
>>> Albuquerque, NM, 87131
>>> (505) 272-4374
>>> [log in to unmask]
>>>
>>>
>>>
>>> -----Original Message-----
>>> From: SPM (Statistical Parametric Mapping) on behalf of Will Penny
>>> Sent: Thu 12/20/2007 9:20 AM
>>> To: [log in to unmask]
>>> Subject: Re: [SPM] questions on perfroming 2 x 2 within-subjects
>>> ANOVA in SPM5
>>>
>>> Dear Michiru,
>>>
>>> This is most easily done using the 'Flexible Factorial'
>>> option.
>>>
>>> 1. Create two factors.
>>>
>>> 2. Call the the first one Subject. Independence Yes, Variance Equal.
>>>
>>> 3. Call the second one 'Condition'. Independence Yes, Variance Unequal.
>>>
>>> 4. Under, Specify Subjects or all Scans, Choose Subjects
>>>
>>> 5. Under Subjects, create a new 'Subject' for each subject that you
>>> have eg. 5.
>>>
>>> 6. Then, for each Subject, under 'Scans'. Enter the 4 scans you have
>>> for each subject.
>>>
>>> 7. Also, for each Subject, under 'Conditions' enter the vector [1:4]
>>>
>>> 8. Under Main effects and Interactions create 2 main effects; factor
>>> 1 and factor 2.
>>>
>>> 9. Specify other covariates as necessary and your o/p directory.
>>>
>>> 10. Then save your design job as 'within_subject_design' and press run.
>>>
>>> I have attached my saved job file 'within_subject_design.mat' as a
>>> template for you. When you run it, SPM should create the design
>>> matrix shown in 'design-matrix.png'.
>>>
>>> Note the 5 subject columns on the left. Without these 5 columns you
>>> do not have a 'within-subject' design.
>>>
>>> Also I have treated your 2 x 2 design as a 1 x 4. So you'll need to
>>> bear this in mind when doing your contrasts eg. 1 1 -1 -1 and 1 -1 1
>>> -1 to test for main effects and 1 -1 -1 1 for the interaction (of
>>> course, pre-pad these with 5 0's).
>>>
>>> Best wishes,
>>>
>>> Will.
>>> Michiru Makuuchi wrote:
>>>> Hi,
>>>>
>>>>
>>>> I have tired to perfrom 2 x 2 within-subjects ANOVA in SPM5, but I
>>>> couldn't find how I could do that in 'Full factorial'
>>> dsign. Therefore
>>>> I designed the design matrix via 'Multiple regression' option. The
>>>> resulted design matrix was similar to Fig 7 of Henson and Penny's
>>>> online document (ANOVA and SPM). The difference was only
>>> the position
>>>> of constant term. In Fig 7, it was the 4th column, but it
>>> was on the
>>>> last column in my design matirix.
>>>>
>>>> Here are my questions.
>>>> Is my approach acceptible for the purpose?
>>>> Can someone point out the exact procedure to build the
>>> model for 2 x 2
>>>> within-subject ANOVA?
>>>>
>>>>
>>>> Best regards,
>>>>
>>>> Michiru
>>>>
>>>> Michiru Makuuchi
>>>> Max Planck Institute
>>>> for Human Cognitive and Brain Sciences Stephanstrasse 1a, 04103
>>>> Leipzig, Germany
>>>>
>>>>
>>> --
>>> William D. Penny
>>> Wellcome Trust Centre for Neuroimaging
>>> University College London
>>> 12 Queen Square
>>> London WC1N 3BG
>>>
>>> Tel: 020 7833 7475
>>> FAX: 020 7813 1420
>>> Email: [log in to unmask]
>>> URL: http://www.fil.ion.ucl.ac.uk/~wpenny/
>>>
>>>
>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------
>>>
>
>
> ------------------------------------------------------------------------
>
--
William D. Penny
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG
Tel: 020 7833 7475
FAX: 020 7813 1420
Email: [log in to unmask]
URL: http://www.fil.ion.ucl.ac.uk/~wpenny/
|