Dear SPM List,
I have some doubts about the results of a full-factorial analysis and want to be sure that I specified the correct design.
I want to compare healthy controls activations with multiple sclerosis patients. These patients can be divided into four sub-group, according to disease phenotype (with progressive gravity).
First, I did a statistical design letting all patients together (full-factorial design with one factor: group, and two levels:controls and patients). I compared activity in patients vs controls by creating the contrast -1 1 and obtained some clusters of differences.
Then, I did again a full factorial design with one factor (group), but with five levels, keeping the patients in four separate groups according to the disease phenotype. In this latter model, I did again a comparison of all patients vs controls by creating the contrast -4 1 1 1 1. In this way, I obtained much more differences than those of previous two-level model.
Why does this happen? Maybe because in the first model I see only differences present in all subjects (a sort of "AND" condition) whereas in the second model I see also differences driven even by one single subgroup (a sort of "OR" condition)? I am not sure if this is the explanation or if there is any other issue that I am ignoring..
Thank you for any advice