Dear Matt,
I would remove the 'group variables' and the 'trial type
variables'.
You can still test for the effect of 'group' using the appropriate contrast.
For example:
(1) The contrast vector c=[ones(1,10),zeros(1,20)] will test for the
effect of group 1 (t-test for positive effect, F-test for any effect).
(2) The contrast matrix C=[ones(1,10),-ones(1,10),zeros(1,10);
zeros(1,10);ones(1,10),-ones(1,10)] will test for a main effect of
group. You'll need the F-test here.
You can also test for the main effect of trial type by using a contrast
that collapses over the relevant columns of the 'group x trial type
interaction' variables.
The main concept here is that if you've got the 'interaction terms' in
your design matrix you can test for the main effects using an
appropriate contrast.
Best wishes,
Will.
Matt Shane wrote:
> 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/
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