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Hi Julian, Given this is an RCT, and given that you aren't interested in "average" effects over the two timepoints, but rather the effect in the follow-up after accounting for the baseline, the best is really simply enter baseline as a nuisance (voxelwise) regressor, and run a two-sample t-test comparing the groups (that is, having the baseline and possibly other nuisance, such as age or sex). There is no need for a repeated measures or mixed design. All the best, Anderson On Tue, 18 Jun 2019 at 06:57, Julian Macoveanu <[log in to unmask]> wrote: > Hi Anderson, > > It is a randomised placebo controlled design. We have a group of patients > assigned to either active treatment or placebo. We want to asses the effect > of treatment vs. placebo. One can say it is from baseline to follow up > while controlling for the placebo effect. By the book, this would just be > the interaction effect baseline and follow-up vs placebo and active. > However, since we know this is not a sensitive design for fMRI data due to > high within subject variability, the idea is that we assume no difference > between subjects at baseline and then just compare the active and placebo > groups at follow-up. But it would be nicer to be able to add the baseline > data as covariates since the assumption that they are the same at baseline > is not waterproof. The latter approach would be justified if we are able to > see that baseline and follow-up scans are indeed correlated. > > Best, > Julian > > On Sun, Jun 16, 2019 at 12:43 AM Anderson M. Winkler < > [log in to unmask]> wrote: > >> Hi Julian, >> >> I'm sorry for the late reply. Was attending conferences. Now I realise >> there is at least one more piece of information missing. What are the >> hypotheses for your two studies? Are you interested in differences between >> baseline and follow-up, or are these two scans intended to improve ability >> to detect effects that would persist across both timepoints? >> >> All the best, >> >> Anderson >> >> >> On Wed, 12 Jun 2019 at 08:52, Julian Macoveanu < >> [log in to unmask]> wrote: >> >>> Hi guys, >>> >>> I would still need some input on the issue below. >>> >>> All the best, >>> Julian >>> >>> On Mon, May 27, 2019 at 10:08 AM Julian Macoveanu < >>> [log in to unmask]> wrote: >>> >>>> Hi Anderson, >>>> >>>> I have not done the correlation yet, how to do it was actually my first >>>> question. The only way I see it, but please correct me if I am wrong, is to >>>> look at one contrast at a time, e.g. I enter the cope1 from one group as >>>> input, and add an voxel-wise EV in the stats which is a 4D made from cope1s >>>> of the respective group at follow-up (in matching order as the input). I >>>> would then look at the contrast to check for any significant effects (+/- >>>> 1). >>>> >>>> Regarding the study design, there are actually two studies we planned >>>> to use this approach on: >>>> - Randomised trial with patients assigned to either real treatment or >>>> placebo >>>> - Remitted patients that that had a secondary episode vs. remitted >>>> patients that did not have a secondary episode after one year. So all >>>> patients scanned at the first remission, and then again after one year. >>>> >>>> Best, >>>> Julian >>>> >>>> >>>> >>>> On Sat, May 25, 2019 at 11:34 PM Anderson M. Winkler < >>>> [log in to unmask]> wrote: >>>> >>>>> Hi Julian, >>>>> >>>>> Could you tell the following: >>>>> >>>>> - How are the correlations between baseline and follow-up computed? Do >>>>> you do some kind of spatial correlation between results, or do you check >>>>> whether task-based BOLD-responses are correlated in both scans? Or >>>>> something else? >>>>> - How are the groups defined? Is this a randomized controlled trial or >>>>> just an observational study of the kind patients vs. controls? >>>>> >>>>> All the best, >>>>> >>>>> Anderson >>>>> >>>>> >>>>> On Fri, 24 May 2019 at 12:50, Julian Macoveanu < >>>>> [log in to unmask]> wrote: >>>>> >>>>>> Hi all, >>>>>> >>>>>> I have 2 groups scanned with fMRI twice. Due to the known high within >>>>>> subject variability which approaches between-subject values, my group >>>>>> decided to first perform a correlation test between baseline and follow-up >>>>>> measurements. If there is a significant correlation between baseline & >>>>>> follow-up then we would like to perform a 2-sample t-test using the >>>>>> follow-up data while adjusting for baseline data. If the correlation test >>>>>> is negative i.e. the baseline cannot predict the follow-up, then we would >>>>>> just do the 2-sample follow-up t-test without baseline correction. Instead >>>>>> we would simply check that whatever we find between groups at follow-up was >>>>>> not present between groups at baseline. >>>>>> >>>>>> Now, the question is, do you think this is a sensible approach? Can >>>>>> the correlation analysis be made in FEAT somehow using voxelwise >>>>>> covariates? I guess if I find the answer to this question I can also move >>>>>> on and similarly adjust the data by the baseline data as covariate. >>>>>> >>>>>> Julian >>>>>> >>>>>> ------------------------------ >>>>>> >>>>>> To unsubscribe from the FSL list, click the following link: >>>>>> https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 >>>>>> >>>>> >>>>> ------------------------------ >>>>> >>>>> To unsubscribe from the FSL list, click the following link: >>>>> https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 >>>>> >>>> >>> ------------------------------ >>> >>> To unsubscribe from the FSL list, click the following link: >>> https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 >>> >> >> ------------------------------ >> >> To unsubscribe from the FSL list, click the following link: >> https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 >> > > ------------------------------ > > To unsubscribe from the FSL list, click the following link: > https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 > ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1