Dear fsl users,

I have 8 control groups and 14 Parkinson disease subjects and after using
siena and sienax i wanted to use the randomise tool in order to localize
where there's a difference in atrophy in these groups..
I've read both the randomize manual (including the example in the practical
instructions) and the Holmes &Nichols paper for nonparametric permutation
test, though i still have a lot of questions about the “translation” of the
results after using the randomise tool. I would really appreciate your help
once more...
My questions are the following:

1)Is it a problem if the number of controls is not the same with the
patients number? if yes is it recommended to reduce the number of patients to 8?
2)The outputs of randomise are 16 different statistics. 4 sienar_tstat, 4
sienar_maxc_tstat, 4sienar_max_tstat and 4 sienar_vox_tstats. If i
understood well, first we check the p-values (which are filtered through
fslview in the range [0.949,1] in order to see p-values <0.05) from
sienar_maxc_tstat1 and sienar_maxc_tstat2 and we detect if there's a group
difference. In your example there are no clusters with voxels in
sienar_maxc_tstat2 with p-value <0.05 while there are some clusters in
sienar_maxc_tstat1 with p<0.05..So this means that the control-patient group
shows a positive value? What would be the conclusions if there were also
clusters in sienar_maxc_tstat2 with p<0.05?  What about the
sienar_maxc_tstat3 and sienar_maxc_tstat4?what kind of info can we extract
from them?
3)The next step is to check the sienar_tstat3 and sienar_tstat4 and
disambiguate what's going on where there's a group difference.Are these
stats corrected for multiple comparisons?  According to your example these
stats gives us the info about what each group is doing separately...when i
load them in fslview independently i see 2 different colors for
sienar_tstat3(red yellow filtered with fslview in a range of [0.5,3].why do
we need to filter the output in this range?and why do we need two colors to
depict them in fslview?these intensities  are definitely not p-values but
what exactly are?) and intensities with bigger magnitude in yellow and lower
magnitude in red...Exactly the same in the sienar_tstat4 with colors blue
and light blue...How can i “explain” these results ? What kind of
information does these sienar_tstats gives us? what about the sienar_tstat1
and sienar_tstat2?what kind of info can we have from them?
4)The cluster threshold in your example is set to 1...why did you choose
this threshold? what's the range of the values that this threshold can
take?Is it a low threshold or a large one?do we have to use more than one
cluster thresholds each time? I read that if we choose a low one we loose
intense focal signals, while if we choose a high one then we loose low
intensity signals..
5)What about the sienar_max_tstats?what kind of information can we extract
from these stats?we use them only to localize the voxels of significance
since this is the weakness of a suprathreshold tests? As for the
sienar_vox_tstats how useful these data can be since there're uncorrected
for multiple comparisons and what kind of info we extract from them?

thanks a lot in advance and i'm really sorry if i tired you with this
extended e-mail but i couldn't find some information to help me on my
previous questions.

Antonios-Constantine Thanellas