Hello,
I am finding that when I use a Z<1.7 to define the cluster size at he highest level analyses, I am getting some interesting activations in regions that I don't see when I use Z<2.3. In both cases I use cluster thresholding and p<0.05 whole brain corrected.....
I know the Z value used to define cluster size prior to correction for multiple comparisons is arbitrary, but is it there any paper that I can use to justify
in my study why a Z<1.7 was used instead of Z<2.3?
Would it be right to say that poststat results with a Z<1.7 are more lenient than with a Z<2.3? I feel it this is not necessarily right but can you please advise?
A second question I have is about poststats as implemented in FEAT....
Say that I have done a lower level analyses - for session, a 2nd level -across session within subjects- and 3rd level -across subjects-
do I need to set up the Z<1.7 at the first and second level and third level analyses - or does FEAT bring the unthresholded data from lower level analyses to the higher levels and then use the Z score specified at the highest level analyses? in other words, will I get the same results if I specify
Z<1.7 across all levels or whether I do Z<2.3 for first and second level and Z<1.7 at the higher level?
Many thanks,
David
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