Hi Martin Thank you very much for your response! To clarify the design: There are 44 subjects, all have been scanned twice and thus have repeated measures of cortical thickness. 22 subjects were first (T0) scanned 2 hours after a placebo treatment. Some days later, the identical subjects were scanned again (T1) but this time 2 hours after a "real" treatment. The other 22 subjects were scanned first (T0) after "real" treatment and then some days later after placebo treatment. The interval between T0 and T1 varies between subjects which I would like to take into account into my analyses. The time between receiving placebo/real treatment and MRI acquisition is identical among all subjects (2hours) and thus not of concern.
Thank you very much for your help! Best, Martina Sent from my iPad > On 21 Apr 2016, at 22:09, Martin Reuter <mreu...@nmr.mgh.harvard.edu> wrote: > > Hi Martina, > > so you don't have a baseline (no treatment) measurement? If you have a > treatment at T0, you mean during an interval before T0, right? But since you > did not scan before that treatment, you cannot quantify that change? The > design is not clear to me. > > About the random effect (with only two time points and two groups) I think > having the intercept is enough. > > Best, Martin > > >> On 04/18/2016 11:51 AM, martina.papme...@puk.unibe.ch wrote: >> Dear FreeSurfer experts >> >> I have one question regarding my data analysis and would be extremely >> thankful for any advice! >> >> My data-set is as follows: I have repeated measures (time point 0 (T0), time >> point 1 (T1)) of several subjects. All individuals underwent an intervention >> at one of the time points and a placebo condition at the other time point in >> a fully randomized fashion. Thus, half of the subjects received treatment at >> T0 and half of them at T1. I am interested in the putative effect of the >> intervention on cortical thickness in a ROI. A major challenge is that the >> time between T0 and T1 varies between individuals and that I expect the time >> to impact on my dependent variable and to likely interact with the condition >> (treatment versus placebo). >> >> I thought about conducting a simple repeated-measures ANOVA. However, as >> stated, I want to take the time between the two sessions into account. I >> also thought about an analysis of rates or percent changes. However, this >> approach does not model the correlation among the repeated measures and is >> thus associated with a reduction in power. >> >> Accordingly, I am trying to use lme models to analyse my data. Since I have >> no between-group variable but a within-subjects design, I am concerned if my >> thoughts are correct and would be grateful for feedback. >> >> I ran the longitudinal FS stream and followed the longitudinal lme model >> tutorial. I propose the following lme model with one random factor: >> thickness = intercept (random factor) + time since baseline + ICV + >> condition (placebo or treatment) + timeXcondition + Age (does not change >> across time interval) + gender >> >> The analysis finishes with 0% non-covergence. Can you tell me if my model is >> suitable given the fact that it is a within-subjects design? I also started >> wondering if it was possible to model time as a random factor but I think >> that I read that this is not suitable if you only have two groups (in my >> case: conditions). >> >> Thank you very much for help and advice! >> >> All best wishes, Martina >> >> >> >> >> Universitäre Psychiatrische Dienste Bern (UPD) >> Universitätsklinik für Psychiatrie und Psychotherapie >> Systemische Neurowissenschaften der Psychopathologie >> Zentrum für Translationale Forschung >> Dr. phil. Martina Papmeyer, Wissenschaftliche Mitarbeiterin >> Bolligenstrasse 111, CH-3000 Bern 60 >> Tel: ++41 0(31) 930 9599, Fax: ++41 0(31) 930 9961 >> Mail: martina.papme...@puk.unibe.ch >> www.puk.unibe.ch >> >> >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer@nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > -- > Martin Reuter, PhD > Assistant Professor of Radiology, Harvard Medical School > Assistant Professor of Neurology, Harvard Medical School > A.A.Martinos Center for Biomedical Imaging > Massachusetts General Hospital > Research Affiliate, CSAIL, MIT > Phone: +1-617-724-5652 > Web : http://reuter.mit.edu > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the e-mail > contains patient information, please contact the Partners Compliance HelpLine > at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail.
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