 |
 |
Hi Stephen, thanks for your reply. I think I understand how to set up group and interaction effects now based on your and Donald's emails. For the time effect, are my input maps the difference between time point 1 and time point 2? I set up the design for the time effect as follows (assuming that the difference maps are the correct inputs) and it didn't work: Effect of time: Group EV 1 1 1 1 1 2 -1 2 -1 contrast 1 Did you suggest it this way - to create 1 EV with group A set to 1 and group B set to -1? If so, should I *not* put values of 1 and 2 for subjects of groups A and B in the group variable (left of EV 1?) ? This is confusing because I thought I need to somehow account for the fact that I have two groups? Is that all done with the following set up?: Effect of time: Group EV 1 1 1 1 1 1 -1 1 -1 contrast 1 Thanks, Maren On Mon, Aug 27, 2012 at 4:00 AM, Stephen Smith <[log in to unmask]> wrote: > Hi - if you want to contrast between the groups, you should use a [1 -1] > contrast with this design. If you want the average result across the two > groups, then in this case you need to use a single EV (with all 1s) - i.e. > use the "-1" option, which is a special case in permutation testing, as > sign-flipping is used to generate the null, instead of timepoint reordering. > > Cheers. > > > > > On 26 Aug 2012, at 21:44, Maren Strenziok wrote: > > Hi, > > Please find attached the design/matrix files for the time effect that > didn't work for me. It would be great if you could take a look and advice. > This is what I got using it with randomise: > > randomise options: -i merged_Post-Pre_N22.nii.gz -o Pre-post -d > design_n22.mat -t design_n22.con -n 500 -T > Loading Data: > Data loaded > 1 permutations required for exhaustive test of t-test 1 > Doing all 1 unique permutations > Starting permutation 1 (Unpermuted data) > Finished, exiting. > > Thanks, Maren > > On Tue, Aug 21, 2012 at 3:29 AM, Stephen Smith <[log in to unmask]>wrote: > >> Hi - sounds like you didn't quite get your design right - if you email >> that into the list someone can comment. >> Cheers. >> >> >> On 20 Aug 2012, at 16:22, Maren Strenziok wrote: >> >> Hi Donald, >> >> I followed your instructions and have a new question. To get the time >> effect, I tried the two samples independent t-test but that didn't work. >> Randomise did not start permuting the data (it finished immediately after >> it started) and the result was a completely empty map. I want to try your >> second suggestion, but I have a question regarding this. You wrote that I >> could also do a one-sample t-test on the difference maps between time point >> 1 and time point 2. I assume that you mean that I make a 4D file with the >> difference maps for all subjects (from the trained and non-trained groups). >> I can do that but wonder whether I would get at the effect of time. For the >> trained group, I expect an effect of time, but not for the non-trained >> group. So if I put them all in the same 4D file, I am worried that my time >> effect will wash out due to inclusion of the non-trained subjects that >> should show no difference over time. >> >> Thanks for your help. Maren >> >> On Tue, Aug 7, 2012 at 2:24 PM, MCLAREN, Donald <[log in to unmask] >> > wrote: >> >>> On Tue, Aug 7, 2012 at 2:06 PM, Maren Strenziok >>> <[log in to unmask]> wrote: >>> > Hi Donald, >>> > >>> > >>> > thanks. Just to confirm, you are saying that I need to do the following >>> > for... >>> > >>> > effect of time: subtract time 1 from time 2 and run a two samples >>> > independent t-test on the difference maps >>> > >>> >>> If you use the contrast of 1/2 1/2 you will get the effect of time, if >>> you use 1 -1, you will get the group*time interaction since the input >>> files are the difference in time. The effect of time could also be >>> estimated with a one-sample t-test. >>> >>> >>> >>> > effect of group: average time 1 and time 2 and run a two samples >>> independent >>> > t-test on the difference maps >>> >>> Correct. The contrast would be 1 -1. This tells you where the task is >>> different in the two groups. >>> >>> > >>> > >>> > I don't understand what you suggest for the interaction effect? Can you >>> > please specify? >>> >>> See above. >>> >>> > >>> > >>> > Thanks, Maren >>> > >>> > >>> > >>> > >>> > >>> > >>> > On Tue, Aug 7, 2012 at 11:32 AM, MCLAREN, Donald < >>> [log in to unmask]> >>> > wrote: >>> >> >>> >> On Tue, Aug 7, 2012 at 7:27 AM, Maren Strenziok >>> >> <[log in to unmask]> wrote: >>> >> > Hi Donald, >>> >> > >>> >> > thanks for you reply. What you describe gets me to the effect of >>> time. >>> >> > What >>> >> > do you suggest to get to the effect of group (and interaction >>> effect) if >>> >> > I >>> >> > have unequal numbers of subjects in each group? >>> >> >>> >> For the interaction, use a two-sample t-test. >>> >> >>> >> For the group effect, you need to average time1 and time2 instead of >>> >> subtracting them. >>> >> >>> >> > >>> >> > Maren >>> >> > >>> >> > >>> >> > On Fri, May 25, 2012 at 11:54 AM, MCLAREN, Donald >>> >> > <[log in to unmask]> >>> >> > wrote: >>> >> >> >>> >> >> On Fri, May 25, 2012 at 10:24 AM, Maren Strenziok >>> >> >> <[log in to unmask]> wrote: >>> >> >>> >>> >> >>> Hi Tom, >>> >> >>> >>> >> >>> after you laid out the 2x2 ANOVA design in a post a few weeks >>> ago, I >>> >> >>> tried it out and wonder what your opinion is on the following >>> >> >>> situation. I >>> >> >>> have scans from two groups (trained, non-trained) and two time >>> points >>> >> >>> (pre-training, post-training). Although each subject has a pre- >>> and a >>> >> >>> post-training scan, I have unequal numbers of subjects in my >>> groups >>> >> >>> (10, >>> >> >>> 12). So when I prepare the difference map required to look at the >>> >> >>> effect of >>> >> >>> group, following your logic, I would first add the map of group A >>> at >>> >> >>> time >>> >> >>> point 1 and group A at time point 2, then add map B at time 1 and >>> map >>> >> >>> B at >>> >> >>> time 2. If I do that I get two files with different volume >>> numbers as >>> >> >>> group >>> >> >>> A has only 10 subjects and group B has 12. When I now subtract >>> these >>> >> >>> maps >>> >> >>> from each other, the result is a difference map that consists of >>> 10 >>> >> >>> volumes. >>> >> >> >>> >> >> >>> >> >> I'm not quite sure I follow what you did, but what you should end >>> up >>> >> >> with >>> >> >> after subtracting time1 from time2 is 22 volumes (1 for each >>> subject). >>> >> >> Essentially, for each subject, you subtract the two time points >>> and get >>> >> >> a >>> >> >> difference image. Then you put those difference images into a >>> >> >> two-sample >>> >> >> t-test (10 in one group, 12 in the other group). >>> >> >> >>> >> >> >>> >> >>> >>> >> >>> Which part of my data was omitted here? The last 2 subjects of >>> group >>> >> >>> two? >>> >> >>> Is this good practice or should I try something else? Also, to >>> >> >>> complicate >>> >> >>> things, I have DTI data that I submitted to the tbss processing >>> stream >>> >> >>> in >>> >> >>> FSL. So in addition to a map with data, I also need a mask file >>> which >>> >> >>> I >>> >> >>> would make from the pooled group I guess. Can you let me know >>> whether >>> >> >>> the >>> >> >>> FEAT GUI to set up the design and matrix files is the better >>> option in >>> >> >>> my >>> >> >>> case? >>> >> >>> >>> >> >>> Any comments are highly appreciated. >>> >> >>> >>> >> >>> Maren >>> >> >>> >>> >> >>> On Tue, May 15, 2012 at 6:00 PM, Thomas Nichols >>> >> >>> <[log in to unmask]> wrote: >>> >> >>>> >>> >> >>>> Dear Ciara, >>> >> >>>> >>> >> >>>> Repeated measures, if you read the list, is quite tricky. >>> Really the >>> >> >>>> best thing is to eliminate any repeated measures and run separate >>> >> >>>> analyses >>> >> >>>> for each contrast of interest. I.e. If the design is >>> >> >>>> >>> >> >>>> A1 A2 B1 B2 >>> >> >>>> >>> >> >>>> then compute the effects for each subject with fslmaths: >>> >> >>>> >>> >> >>>> Main effect of A vs B: (A1+A2)-(B1+B2) >>> >> >>>> Main effect of 1 vs 2: (A1+B1)-(A2+B2) >>> >> >>>> Interaction: (A1-A2)-(B1-B2) >>> >> >>>> >>> >> >>>> Then you'll have reduced your data to a set of 24 images which >>> you >>> >> >>>> can >>> >> >>>> submit to a one-sample t-test. >>> >> >>>> >>> >> >>>> Does this help? >>> >> >>>> >>> >> >>>> -Tom >>> >> >>>> >>> >> >>>> >>> >> >>>> On Tue, May 15, 2012 at 7:16 PM, Ciara Greene >>> >> >>>> <[log in to unmask]> >>> >> >>>> wrote: >>> >> >>>>> >>> >> >>>>> Hi FSL users, >>> >> >>>>> >>> >> >>>>> I'm a bit confused as to how to go about implementing a 2x2 >>> repeated >>> >> >>>>> measures design in randomise. >>> >> >>>>> >>> >> >>>>> I have resting state data from 24 subjects under 4 conditions - >>> 2 >>> >> >>>>> factors, each with 2 levels - each of which was acquired in a >>> >> >>>>> separate run. >>> >> >>>>> I have conducted concat ICA on this data and now want to >>> compare ICs >>> >> >>>>> across >>> >> >>>>> the different scanning conditions using dual regression. I >>> >> >>>>> understand that >>> >> >>>>> implementing repeated measures designs in randomise can be >>> tricky; >>> >> >>>>> is there >>> >> >>>>> a way to extend the 1 factor/4 levels design described at >>> >> >>>>> >>> http://www.fmrib.ox.ac.uk/fsl/randomise/index.html#Ex:RepeatMeas to >>> >> >>>>> examine >>> >> >>>>> main effects of factor 1 and factor 2 and their interaction? >>> >> >>>>> >>> >> >>>>> Thanks for your help, >>> >> >>>>> Ciara >>> >> >>>> >>> >> >>>> >>> >> >>>> >>> >> >>>> >>> >> >>>> -- >>> >> >>>> __________________________________________________________ >>> >> >>>> Thomas Nichols, PhD >>> >> >>>> Principal Research Fellow, Head of Neuroimaging Statistics >>> >> >>>> Department of Statistics & Warwick Manufacturing Group >>> >> >>>> University of Warwick, Coventry CV4 7AL, United Kingdom >>> >> >>>> >>> >> >>>> Web: http://go.warwick.ac.uk/tenichols >>> >> >>>> Email: [log in to unmask] >>> >> >>>> Phone, Stats: +44 24761 51086, WMG: +44 24761 50752 >>> >> >>>> Fax: +44 24 7652 4532 >>> >> >>>> >>> >> >>>> >>> >> >>> >>> >> >> >>> >> > >>> > >>> > >>> >> >> >> >> >> --------------------------------------------------------------------------- >> Stephen M. Smith, Professor of Biomedical Engineering >> Associate Director, Oxford University FMRIB Centre >> >> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK >> +44 (0) 1865 222726 (fax 222717) >> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve >> >> --------------------------------------------------------------------------- >> >> >> >> > <design_n22.fsf><design_n22.con><design_n22.mat> > > > > --------------------------------------------------------------------------- > Stephen M. Smith, Professor of Biomedical Engineering > Associate Director, Oxford University FMRIB Centre > > FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK > +44 (0) 1865 222726 (fax 222717) > [log in to unmask] http://www.fmrib.ox.ac.uk/~steve > --------------------------------------------------------------------------- > > > >