Hi Gang,
Nope, the "anode" did not mean a voxel or an anatomically or statistically defined region. The "anode" is one condition of within-subject variable "CiJi". Similarly, the "QainHou" (two level: after vs before) and the "Contrast3" (two level: now vs notnow) variables are within-subject variables.
In the current LME model, effect of this Lable is significant: -gltLabel 6 after_before_in_anode_now -gltCode 6 'CiJi : 1*anode QainHou : 1*after -1*before Contrast3 : 1*now' \. That is to say, in the "anode" "now" condition, there was a significant difference between "after" and "before" conditions. Therefore, I tried to extract the data in the "anode" "now" condition for "after" and "before" condition separately, then data were fed into a paired t-test. However, t-test revealed that group comparison between "after" and "before" conditions on the data was not significant. I guess one reason for 'not significant in the t-test, but significant in the LME' is that: in the LME, the model was modelling many effects, including interactions and main effects of 'CiJi', 'QainHou', 'Contrast3', and main effects of age, education. In contrast, in the t-test, these effects were not modelled. Is that correct?
So is there any method to extract the only/simple effect of 'after' - 'before' in the 'anode' 'now' condition while regressing out interactions and main effects of 'CiJi', 'QainHou', 'Contrast3' (these were within-subject variables)?
Thanks.
All the best.
Rujing
