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Hi JF, Please, see below: On 16 December 2016 at 15:50, Jean-Francois Cabana <[log in to unmask]> wrote: > Dear FSL experts, > > > > I have a question concerning the design matrix and contrasts for use in > PALM. Here is a short description of my problem. We are studying a group of > subjects that are all affected with a particular genetic mutation, and we > are comparing several MRI metrics to a group of age- and sex-matched > healthy controls. Furthermore, the subjects group can be divided into two > subgroups, because the women are clinically affected differently than men > (dyslexia and epilepsia respectively). I’d like to compare each of the > three groups between themselves, but also compare the full subjects group > (Female+Male) vs control. > > > > When I first started my analysis, I did a simple ROI analysis using a > two-tailed two-group t-test with additional nuisance variables added to the > model (age, age², sex, age*sex, age²*sex) to compare healthy control vs all > subjects with the mutation. I get a set of p-values for this test. Now I > switch to the 3 groups case where I split the subjects into F and M. Let > EV1, EV2 and EV3 be the variables representing healthy controls, subjects-F > and subject-M respectively. I set up my two-tailed contrast matrix as this : > > > > [-2 1 1 0 0 0 0 0; ... % HC vs (F+M) > > -1 1 0 0 0 0 0 0; ... % HC vs F > > -1 0 1 0 0 0 0 0; ... % HC vs M > > 0 1 -1 0 0 0 0 0]; % F vs M > > > > Now, my question is regarding to the first contrast here. I would (perhaps > naively) expect that the first contrast of this 3 groups design would be > equivalent to the earlier 2 groups design, where F and M were considered as > a single group. However, the p-values I get appears to be generally higher > in the 3-groups analysis. Setting p<0.05 as a significance threshold, I > then get fewer significant results in the 3-groups version. > > > > Here are my questions : > > > > First, does this contrast here make sense for the combination of the F+M > groups? > Yes. > > > Second, how do you interpret the difference in p-values between the two > designs? > The design that has 3 groups accommodates (discounts) the possibility that M and F could have different effects and different sample sizes, whereas the other one, with 2 groups only, doesn't allow for that. > > > And finally, would you recommend using the 2-group design to compare the > full subjects group vs controls, and then the 3-groups design to compare > all subgroups, or would you rather trust the 3-group design for all > statistics, including the combination of the F+M groups? > If the two groups had/have the same size and if it were known that M and F had the same effects, then lumping these two would be fine. However, that doesn't seem to be the case (e.g., different effects of epilepsy and dyslexia), so I would suggest keeping these separate. All the best, Anderson > > > > > Thank you for your help, > > JF >