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Dear all, the answer is still - weight your subject columns, if your groups are of unequal size and/or you want to test non-differential effects. If your design matrix includes subject columns, then it will become rank deficient (the rank would be that of a full factorial design based on your conditions/groups). Therefore, the condition/interaction columns can only be tested for effect size if you include the portions of effect size that are modelled by your subject columns. The subject weights cancel out only if you test a differential contrast over groups of equal size. Hope this helps, Volkmar Quoting Matt Shane <[log in to unmask]>: > Not to beat a dead horse, but given that my question has spawned > quite a discussion and identified several other people with the same > problem, I thought I'd add a bit more to the ongoing discussion. I > thought I'd also explicitly ask whether or not this might be a bug > in SPM5. Has anyone else encountered this problem as well? Has > anyone *not* encountered this problem when using the > flexible-factorial design? > > Anyone who has followed this thread may not need to reread the gory > details of my setup and problem. And so I'll restate it only very > briefly. My .mat file is also attached. > > My design (which is very much like Darren's) used a > flexible-factorial design with 3 factors: Subject, Group and > TrialType. Independence: yes, yes, no; Variance: equal, unequal, > unequal. My resultant condition matrix (which is also set up almost > the same as Darren's, except that I have 3 groups) is: > > [ 1 1 > 1 2 > 1 3 > 2 1 > 2 2 > 2 3] > > I have explicitly modeled a main effect of Subject (as I believe is > necessary to make it a within-subject design), and also a Group x > TrialType interaction. > > The problem occurs at the level of the contrast manager. In short, > it seems to me that: > > 1. Any contrast that does not balance the positive and negative > values is said to be 'invalid'. (ie. any contrast against the > implicit baseline cannot be performed) > > 2. Any contrast that spans across Factors in the design matrix is > 'invalid'. Thus: > > Contrasting Subject 1 to Subject 23 is VALID > Contrasting TrialType 1 to TrialType 3 is VALID > Contrasting Group 1 to Group 2 is VALID > > Contrasting Group 1/TrialType 1 to Group 1/TrialType 2 is INVALID > Contrasting Group 1/TrialType 1 to Group 2/TrialType 1 is INVALID > > I believe that the second problem is actually a subset of the first > problem. That is, I think that any contrast in which the positive > and negative values are not balanced *per factor* will be marked as > invalid. Darren: I think this explains why your 1 0 -1 -1 0 1 > contrast was valid, but your 1 1 1 -1 -1 -1 contrast was not. > > So we're further along in defining the problem...anyone have any answers? :) > > Best, > 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 d gitelman > Sent: Thu 1/3/2008 6:58 AM > To: [log in to unmask] > Subject: Re: [SPM] questions on perfroming 2 x 2 within-subjects > ANOVA in SPM5 > > Dear Boris, Volkmar, SPM > > I had found your posting but this does not work for me and produces the > message invalid contrast. Just to give a bit more information on the > flexible factorial setup. > > The order of factors (going down in the batch box) is subject, group, > condition. Independence is yes, yes, no. Variance is equal, unequal, > unequal. > > I have specified the design by subject. For each subject in the first group > (n=9) the condition matrix is > > [1 1; 1 2; 1 3] which gives [ 1 1 > 1 2 > 1 3 ] > > > Similarly for the second group (n=12) I used [2 1; 2 2; 2 3] > > There is a main effect of subject (factor number 1) > There is an interaction of group x condition (factor numbers 2 3) > > This produces the design I previously attached which has 21 columns for the > subject effects (each with 3 rows), 3 columns of group 1 x condition and 3 > columns of group 2 x condition. > > Entering a contrast of 2*1/9*ones(1,9) 2*1/12*ones(1,12) 1 1 1 -1 -1 -1 is > invalid > I've also tried substituting 3 for the 2 above, 2/3 and 3/2 or leaving off > the 2 entirely. All are invalid. > > The contrasts zeros(1,21) 1 -1 0 1 -1 0 or zeros(1,21) 1 0 -1 -1 0 1 > are valid. > > ------------------------ > Have I set this up differently than you did? > > When accounting for the subject means why is there a factor of 2 included? > > ------------------------ > > As a separate but related question for flexible factorial designs, how does > one use the repl condition? > > 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: boris suchan [mailto:[log in to unmask]] >> Sent: Thursday, January 03, 2008 3:51 AM >> To: 'd gitelman' >> Subject: AW: [SPM] questions on perfroming 2 x 2 >> within-subjects ANOVA in SPM5 >> >> Hi Darren, >> try 2*1/N1*ones(1,N1) 2*1/N2*ones(1,N2) 1 1 -1 -1 this was >> from a post by Volkmar Glauche >> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind0709&L=SPM&P=R2 >> 1228&I=-3&X=2D >> 3AC4620A117A0F02&Y=boris.suchan%40rub.de >> >> and for me it worked... >> best wishes >> boris >> >> Priv.-Doz. Dr. Boris Suchan >> Institute of Cognitive Neuroscience >> Ruhr University Bochum >> Universitätsstr. 150 >> 44780 Bochum >> GAFO 05/613 >> Tel.: + 49 234 3227575 >> Fax: + 49 234 3214622 >> mailto: [log in to unmask] >> http://www.ruhr-uni-bochum.de/neuropsy/mitarbeiter/boris_suchan.html >> > -----Ursprüngliche Nachricht----- >> > Von: SPM (Statistical Parametric Mapping) >> [mailto:[log in to unmask]] >> > Im Auftrag von d gitelman >> > Gesendet: Mittwoch, 2. Januar 2008 20:44 >> > An: [log in to unmask] >> > Betreff: Re: [SPM] questions on perfroming 2 x 2 >> within-subjects ANOVA >> > in >> > SPM5 >> > >> > 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 >> > >> > ---------- >> > 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/ >> > > >> > > >> > > >> > > >> > > >> > >