Thanks,

what I mean is in order to quantify a treatment effect for the subjects that received treatment at T0, you would need another scan before that (Tminus1). You would need three time points:

group1: baseline, placebo, treatment group2: baseline, treatment, placebo

you could then test if treatment or placebo differs from baseline.

If you assume that the ordering is not important, you could use a binary variable (drug / placebo) instead of time in LME and control for the time delta as a co-variate. This may make sense, as you are not really interested in change / time unit.

Another model would be to use time as usual in LME and add drug as a time varying covariate. I am not a statistician, so I don't really know what would be best in your case.

Cheers, Martin

On 04/21/2016 06:08 PM, Martina Papmeyer wrote:

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 <mreuter@nmr.mgh.harvard.edu mailto:mreuter@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.papmeyer@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.Papmeyer@puk.unibe.ch www.puk.unibe.ch

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-- 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 mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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