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March 18, 2019 at 08:14 GMT+0000 in reply to: Mixed model specification and centering of predictor #346
Thanks for the explanation. Helped a lot. I decided to go for the
m2with interaction in the random slopes.
As a next step I would like to introduce
timeas another IV. I have the baseline EEG resting state recording (
time 0) and a post treatment EEG recording (
time 1) as well as pre- and post-distress scores. I wonder, due to the fact that I just have two time points, that
distressmight be a mediating variable. I haven’t found anything about mediation in the documentation, so I wonder if there is a recommended package by you Henrik?
Thanks again!!March 4, 2019 at 13:26 GMT+0000 in reply to: Mixed model specification and centering of predictor #342
Thank you for your fast reply! At the same time, my hopes are crushed.
I’m working with a disease that causes alternation in the resting state EEG pattern. In the literature, however, it has not yet been possible to make a clear statement as to which alternation takes place in which brain region. In addition, the experience of the disease can alter a lot between individuals, which results in quiet a heterogeneous EEG pattern. Therefore, I think the approach of using not only the patient but also the electrodes as random effects might be more appropriate. But I haven’t found anything in the literature yet. In addition, I use a questionnaire which records the distress of this disease (and hopefully is mirrored in the EEG pattern).
The dependent variable Power contains the EEG measure. I am interested if this measure depends on distress (questionnaire – continuous variables) and FrB (8 frequency bands, factorial), as well as duration of the disease. Random effects are PatID (participants) and Electrodes (65)
m1 <- mixed(Power ~ FrB * Distress + Duration + (FrB | PatID) + (1 | electrodes), data, method=”S”)
As far as I experienced it, other studies are working with electrode clusters (and not single electrodes). This would result in my opinion in:
m2 <- mixed(Power ~ Cluster * FrB * Distress + Duration + (FrB + Cluster | PatID), data, method=”S”)
What do you think?March 4, 2019 at 11:22 GMT+0000 in reply to: Mixed model specification and centering of predictor #339
I stumbled upon this post with great curiosity. Since I also work with EEG, but under a somewhat different, but nevertheless similar approach, I wondered whether there is a published paper to your computations and considerations?
@Henrik, please excuse me for using your forum for such a purpose.
@cbrnr, please excuse my direct request, but your help would be a great support.
- This reply was modified 1 year, 3 months ago by SeeArrr.