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Hello Gwenaelle, Thank you again...I chose the ANOVA because of some people told me it was more correct than t-test, but if you tell me it's ok for my model i'll choose 2 sample ttest unpaired, then. :) I have signifficant results with corrected option in randomise, is necessary run -x option in this case? Bests regards, Patricia. 2010/11/25 Gwenaëlle DOUAUD <[log in to unmask]> > Hi Patricia, > > it looks ok to me, though I am not sure why you would choose to follow the > second model rather than the first one based on the previous answer, > especially if you're only looking at the contrasts between the healthy group > and every other disease group... You might want to add the -x option in > randomise to output the uncorrected p-values. > > Cheers, > Gwenaelle > > > De: Patricia Pires <[log in to unmask]> > Objet: Re: [FSL] Re : [FSL] Glm > > À: [log in to unmask] > Date: Mardi 23 novembre 2010, 9h55 > > Hi Gwenaëlle, > > thanks for your quick reply. Then I assume second approach is better than > the first one for my model. > > I would be safe if I have done well, could you please help me with this? > > I have 4 groups to contrast FA values: > > 1.- Healthy (EV3) > 2.- Disease 1 (EV1) > 3.- Disease 2 (EV4) > 4.- Disease 3 (EV2) > > > If i choose second approach i have to run in Glm an ANOVA 4-group unpaired > and not a t-test (as it would be the case of the firts approach), is that > right? > > My principal question is about the design matrix. I think that I have run > well the EV's (4 EV's with their respectives 1 and 0 according to their > corresponding group). I didn't add any covariate. > > However I am not pretty sure if i did well in the "Contrast and F-test" > option: > > I did 6 contrast --> > > /ContrastName1 Healthy (EV3) > Disease1 (EV1) > /ContrastName2 Healthy (EV3) < Disease1 (EV1) > /ContrastName3 Healthy (EV3) >Disease2 (EV4) > /ContrastName4 Healthy (EV3) <Disease2 (EV4) > /ContrastName5 Healthy (EV3) >Disease3 (EV2) > /ContrastName6 Healthy (EV3) <Disease3 (EV2) > * > * > Matrix > > EV1 EV2 EV3 EV4 > > -1.000000e+00 0.000000e+00 1.000000e+00 0.000000e+00 > 1.000000e+00 0.000000e+00 -1.000000e+00 0.000000e+00 > 0.000000e+00 0.000000e+00 1.000000e+00 -1.000000e+00 > 0.000000e+00 0.000000e+00 -1.000000e+00 1.000000e+00 > 0.000000e+00 -1.000000e+00 1.000000e+00 0.000000e+00 > 0.000000e+00 1.000000e+00 -1.000000e+00 0.000000e+00 > * > * > I have not selected anything in the F-test option (i.e. F-test=0). Is that > correct? > > Then I saved the matrix. > * > * > Next, I have run randomise with this format: > * > * > > randomise -i all_FA_skeletonised.nii -m mean_FA_skeleton_mask.nii -o > resultados_TBSS -d matriz.mat -t matriz.con -n 5000 --T2 -V > * > * > Did I follow well all procedures? I appreciate very much your help. > > Bests regards, > > Patricia. > > > > 2010/11/16 Gwenaëlle DOUAUD <[log in to unmask]<http:[log in to unmask]> > > > > Hi Patricia, > > here is what Tom (Nichols) said on this earlier this year: > > "The only difference between the two approaches is the assumption of common > error variance over the 3rd group if included (possibly bad), and a > corresponding increase in DF (always good). > > So there's no right answer... > > The safe way is to only study the data needed (2nd approach) because if it > happens that group C has wildly smaller variance you can get inflated > significances (or reduced power if it has wildly larger variance, but still > not 'accurate' inferences relative to 'truth'). > > However, if the 'master' inference is determined by the F-test across all > groups, then it's fine to work with the big model - 1st approach - since > you're depending on it's validity anyway." > > Hope this helps, > Gwenaelle > > > > -------------------------------------------------------------------- > > Gwenaëlle Douaud, PhD > > FMRIB Centre, University of Oxford > John Radcliffe Hospital, Headington OX3 9DU Oxford UK > > Tel: +44 (0) 1865 222 523 Fax: +44 (0) 1865 222 717 > > www.fmrib.ox.ac.uk/~douaud > > -------------------------------------------------------------------- > > > >