Hi,

You can see how the error in the p-value relates to the number of permutations on the wiki:
  http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Randomise/Theory#Monte_Carlo_Permutation_Tests

All the best,
Mark



On 27 Feb 2014, at 08:13, Alain Imaging <[log in to unmask]>
 wrote:

Thanks a lot Mark.

Sometimes the simplest answer is the one I'm not able to see, apparently.
I will go for a smaller number of permutation (any hint for the minimum number that still will give me some "proxy" results ?).

Best

Alain 

> Date: Thu, 27 Feb 2014 06:34:55 +0000
> From: [log in to unmask]
> Subject: Re: [FSL] fastest way to check vertex analysis results
> To: [log in to unmask]
> 
> Hi,
> 
> You can run randomise with a smaller number of samples, which will speed it up. The results will be less accurate (the p-values will vary) but it will let you see if you have anything near the threshold or not.
> 
> All the best,
> Mark
> 
> 
> On 24 Feb 2014, at 11:00, Alain Imaging <[log in to unmask]> wrote:
> 
> > Dear all,
> > 
> > I would like to have an hint on a rather practical question.
> > 
> > I'm conducting exploratory analysis between several behavioral measures of the same construct and shape using vertex analysis.
> > What I would like to know is if there is a quick method to check if it could be valuable perform a (time consuming) randomise for a certain behavioral measure.
> > I can only think to running randomise with inference off (but then, to which distribution compare the t ?) or performing the old shape analysis using --surfaceout and performing the fdr correction.
> > Are there any other methods less time consuming than randomise ? And if not, which of the two methods that I outlined is the most suitable and will give me the best idea of the results of randomise ?
> > 
> > Thanks in advance
> > 
> > Best
> > 
> > Alain