Cluster-forming threshold in SnPM

[Hill, Donal]

Dear experts,

I have been comparing the results of paired t-tests using SnPM and FSLs randomise. In both instances, I am comparing cluster extent results, where I use the “-c <thresh>” option in FSL.

When using FSL, you have to provide a t-statistic threshold as the value of <thresh>. However, within SnPM, the user provides an uncorrected p-value as input. I am therefore having trouble setting my SnPM and FSL analyses up to use exactly the same cluster-forming threshold.

When I run SnPM with a p < 0.001 threshold, I see the initial output:

Initialising...
Working on correct permutation...
Warning: Pseudo-T cluster-forming threshold defined by P-value using Gaussian approximation P=0.001 -> Z=3.0902; actual
Pseudo-T threshold unknown but may be higher than 3.0902.

where the Z value is what I would expect for such a p-value. I don’t know, however, what T value SnPM has settled on using. I would like to know this information, so that I can use precisely the same t-statistic threshold within my FSL analysis.

Any help would be fantastic!

Kind regards,
Donal

[Hill, Donal]

Hi again,

Sorry for the noise! I realise now that SnPM can also take T-stat thresholds as input. Just means I have to rerun everything ;)

Cheers,
Donal

[Thomas Nichols]

That's right! Use either p-value or statistic value to specify the cluster forming threshold.

-Tom

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[wang.z...@gmail.com]

But which value is suitable for the Cluster-forming threshold in SnPM?
0.001 or 0.0001?

[Thomas Nichols]

The great thing about the non-parametric approach is that *any* threshold is valid. However if you use a threshold much below P=0.01 you may find that the clusters (even if significant) are too large to be useful. 

-Tom

__________________________________________________________

Thomas Nichols, PhD
Professor of Neuroimaging Statistics

Oxford Big Data Institute

Li Ka Shing Centre for Health Information and Discovery

Nuffield Department of Population Health

University of Oxford

Email: thomas....@bdi.ox.ac.uk

Web (interim): http://warwick.ac.uk/tenichols

To view this discussion on the web, visit https://groups.google.com/d/msgid/snpm-support/15f70b98-9d40-49fe-a90d-18c763c7d232%40googlegroups.com.

[wang.z...@gmail.com]

Thanks, Prof. Nichols,

But which threshold of p_unc for cluster forming is suggesttive most?
The website of snpm tells "For cluster-wise inference with p < 0.05 FWE corrected using a cluster-forming threshold of p < 0.0001", that means, 0.0001 is recogmended?

[Thomas Nichols]

No no! That was juat an example. For reference, SPM uses a cluster forming threshold of uncorrected P=0.001 and FSL used to use P=0.01. You may want to look at Woo & Wager that suggest P=0.01 gives clusters that are too large to interpret & instead recommend P=0.001 (but I've also heard push back from users that P=0.001 can lack sensitivity, so it's not a settled issue).

-Tom

__________________________________________________________

Thomas Nichols, PhD
Professor of Neuroimaging Statistics

Oxford Big Data Institute

Li Ka Shing Centre for Health Information and Discovery

Nuffield Department of Population Health

University of Oxford

Email: thomas....@bdi.ox.ac.uk

Web (interim): http://warwick.ac.uk/tenichols

To view this discussion on the web, visit https://groups.google.com/d/msgid/snpm-support/1ab92b6d-388c-4fb7-9dd1-26ea0a7143c9%40googlegroups.com.