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
------
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
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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/
>
>
>
>
>
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