Dear experts,
I have 2 groups, 3 time points DTI data and one covariate (education), and would like to see the effects of group and sex on longitudinal changes of FA.
(1) Concerning the preprocessing, I just put all the FA images from all subjects at all time points together and did the regular tbss pipeline.
However, my DTI data is unbalanced, around half of the subjects only have 1 or 2 time points.
I wonder whether the mean skeletonized FA would be biased towards the subjects with more data points and whether it would be better to create the mean skeleton using only one time point (first time point?) for each subject?
(2) For the statistical analysis, I basically created the design matrix and exchangeability blocks following the examples in other posts. Is it correct to add an EV as bellow to specify the effect of education?
sub timepoint EV1 EV2 EV3(edu)
1 1 1/2 0 10
1 2 1/2 0 -10
2 1 -1/3 1/3 7
2 2 -1/3 1/3 -7
2 3 -1/3 1/3 0
(3) I am also a bit confused with the options in PALM. If I understand correctly, -npc, -corrcon, -fdr are used for multiple simple-effect tests correction. Which one of the three should I use? What is the default if I do not specify any of them? Should I also add -T (tfce) if I want to apply TFCE on FA images or tfce will be done by default for DTI data? There are also two options -ee, -ise you can use in PALM, but how to test whether my data fit either ee or ise?
I would appreciate any suggestion you could provide.
Ling
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