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Dear Camille, there is one likely explanation for the increase of the number of significant voxels in an ANOVA with multiple conditions compared to a series of one-sample t-test: the ANOVA model has much higher degrees of freedom (if I'm right there should be 27 for 10 subjects and 4 conditions) than the one-sample t-test (9). There are other differences between the two models as well: in a one-sample t-test the only source of variance is between-subject, whereas in the ANOVA model there is both between-subject and within-subject variance. To compare 2 conditions, one could even model differences between conditions on the 1st level and take the resulting con images to the 2nd level. (This holds for any t-contrast that can be computed on 1st level.) There is a lot more to say about the implications of different models on the results, but as a rule of thumb you should only include those conditions in your 2nd level that you are using in your contrasts. Volkmar Am Dienstag, den 27.01.2009, 17:22 +0000 schrieb Camille Maumet: > Dear SPMers, > > I have 10 subjects and 4 different conditions. First level stats give me one > contrast image per subject per condition. My question arises with the > second-level statistical analysis. I want to find the effect of each > condition on my group of subjects. > > I first performed four different one-sample t-test to test each condition on > my group of subjects. This worked fine, however I thought that it would be > better to use a one-way ANOVA (flexible factorial) in order to take into > consideration the effect of each subject. > > To this aim, I used the "flexible factorial" design with two factors : > subject and condition and two main effects subject and condition. To isolate > the effect of one condition I used the following T-contrasts : > Condition 1 : [ones(1,10)/10 1 0 0 0] > Condition 2 : [ones(1,10)/10 0 1 0 0] > Condition 3 : [ones(1,10)/10 0 0 1 0] > Condition 4 : [ones(1,10)/10 0 0 0 1] > > The ANOVA leads to much more voxels activated with a FWE-corrected threshold > than the solution using 4 different one-sample t-test. I wonder if that can > be explained by the fact that subjects variability have been identified in > the model ? > > Furthermore, I wonder if this approach is right on a statistical point of > view ? I searched the mailing list and only found examples in which one-way > within-subject ANOVA was used for conjunction analysis or difference > between-conditions. > > Any thought on this would be highly appreciated, > > Camille > -- Volkmar Glauche - Department of Neurology [log in to unmask] Universitaetsklinikum Freiburg Phone 49(0)761-270-5331 Breisacher Str. 64 Fax 49(0)761-270-5416 79106 Freiburg http://fbi.uniklinik-freiburg.de/