Hi K,
I would recommend to use the data from the longitudinal directories also for the cross sectional analysis. That data will be less noisy than from independent processing (which is what you also find).
Since the longitudinal stream goes through many different processing steps than the regular pipeline measurements are not directly comparable between the two pipelines. For example the longitudinal pipeline has an additional interpolation step that changes the images. Also surfaces are allowed to go through additional fine tuning steps. This explains why measurements are different between the streams.
Anyway, the increased precision is always a good thing and you can profit from that for reporting the cross sectional findings.
Best, Martin
Am 20.08.2017 um 17:58 schrieb K:
Good morning Martin et al.,
We are analyzing cortex and subcortical volumes for 2 groups with (mostly) 2 scans per participant. We want to report longitudinal findings as well as cross-sectional group differences at each of the 2 time points. For the time point 1 and time point 2 analyses, does it make sense to use the longitudinal stream-processed data, or is it better to use the cross-sectional stream for each time point independently?
For example: Comparing the brain stem volumes for individual participants using longitudinal vs cross-sectional data for time point 1, we notice some differences (cross-sectional volumes tend to be 95-98% as large, varying), and group differences are more pronounced when using the longitudinal data (i.e., some structures did not show significant group differences in volumes using cross-sectional data, but did show significant differences using longitudinal).
I know you have written about reduced variability and better precision with the longitudinal stream, but we weren't sure if this also applied to using it only at one time point to report cross-sectional findings.
Appreciate your guidance!
K
Additional keywords: longitudinally, cross-sectionally, single time point, benefits, advantages, drawbacks, cortical thickness, surface area, volumetric
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