On Di, 2018-03-13 at 21:48 +0100, lanbo Wang wrote:
> Dear Kersten,
> Thanks, I find it. And I have other questions:
> 1. The intercepts all set as one, so in this model it doesn't
> separate different subjects, or can say no individual subject change
If I understood correctly, the question is whether or not we can get
estimates for individual slopes across time?
If so, then yes, that's possible - but I'd have to run an analysis
myself and look up how to do it exactly - I'll get back on this.
> 2. Should we set age according to different timepoint, or just use
> baseline age?
It's better to use age at baseline.
One of the nice things of the LME is that it can separate the cross-
sectional effect of age (at baseline) and the longitudinal effect of
aging (=effect of time). So the aging effect is already incorporated
within the 'time since baseline' variable, which of course should also
be present in the model.
Since it is difficult to estimate and interpret effects that are very
redundant (such as time vs age at each timepoint), it's better to just
use age at baseline for the other regressor.
> On Tue, Mar 13, 2018 at 3:34 PM, Diers, Kersten /DZNE <Kersten.Diers@
> dzne.de<mailto:kersten.di...@dzne.de>> wrote:
> Hello Lanbo,
> the univariate example data can actually be downloaded from the LME
> tutorial website:
> Search for: "An optional sample dataset which can be used to become
> familiar with the LME Matlab tools can be found here". The linked
> tar.gz archive contains two folders, one for the univariate and one
> the mass-univariate example data.
> Best regards,
> On Di, 2018-03-13 at 13:38 +0100, lanbo Wang wrote:
> > Dear Experts,
> > Hi,
> > There is no example detail on website of LME tutorial. I have some
> > question about it.
> > Could you send me the table of ADNI univariate example data?
> > Thanks,
> > Lanbo
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