Hi Alan,
I'd say it depends on what the study is about, but in principle, I'd
think that the covariates should remove what would have potential to be
confounding more what the main effect would be. In the example of
schizophrenia, I'd choose BrainSegVolNotVent, and run both models, with
and without it, and interpret the results combined.
Also, unless if the samples are too small or unless one wants to
explicitly test the effect of ICV and/or BV, I don't see any problem in
including both ICV and BV in the model, even considering they are well
correlated to some extent. The shared variance between them interferes
on the beta-estimates for them, but not on the betas for the other
regressors that you would be testing, and the part of the variance that
is not shared between them will absorb the effects for which they were
chosen to be covaryied out.
This is my opinion. Others may think differently.
All the best!
Anderson
On 24/08/11 12:51, Alan Francis wrote:
Hi Anderson:
Your explanation is very well put. I have a question. Suppose one is
looking at High Risk datasets (for example Schizophrenia) where the
brain morphological alterations are subtle but spread across the
brain, which covariate would you use?
thanks,
Alan
[Beth Israel Deaconess Medical Center]
On Wed, Aug 24, 2011 at 12:43 PM, Anderson Winkler
<[email protected] <mailto:[email protected]>> wrote:
A side note: If you are using FS 4.5.0 or earlier, there is also
BrainSegVolNotVent, which discount ventricles. If you want to
capture effects of aging or atrophy, perhaps this could be more
sensitive than BrainSegVol.
On 24/08/11 12:32, Anderson Winkler wrote:
Hi Zuzana,
Yes, you can use BrainSegVol as a measurement of brain volume
(I'd assume you are using FS <=4.5.0). Note that there is another
measurement that you might be interested in, the IntraCranialVol.
These measurements tell different things and not necessarily
correlate well one with another depending on the sample. BSV
considers the voxels labelled as GM and WM, including subcortical
structures and cerebellum and so, it correlates better with
amount of GM and WM and tends to be more sensitive to pathology,
atrophy and aging. ICV is more robust to these effects. You may
want to choose the one that is more appropriate to your study.
Also, if you are considering brain volume as a covariate for
cortical thickness, it's not necessary. Thickness correlates
poorly with brain volume, and these two things are not correlated
genetically.
Hope this helps!
All the best,
Anderson
On 24/08/11 05:39, zuzana nedelska wrote:
Hello,
I have a question about calculating brain volume (in mm3) when
performing recon-all.
Do I take brainseg volume in the analysis stream line as
subject's brain volume (in mm3)?
Thank you for reply.
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