[FieldTrip] Query regarding stat.prob and permutation tests

[Schoffelen, J.M. (Jan Mathijs)]

Hi Cihan,

cfg.computeprob is an option that is used by (some of) the ’statfuns’, to convert a test-statistic with a known shape into a p-value, based on the shape of the parameter, (e.g. a T or F statistic).

The computational algorithm with which the p-value is computed (+returned in the output of a high level function call to ft_timelock/freq/sourcestatistics) depends on a combination of the contents of cfg.method (indeed if you would use cfg.method=‘montecarlo’, then the returned p-values are based on a permutation test, if you would  use cfg.method=‘analytic’ the p-values will be based on the known distributions), and cfg.correctm.

I  hope that this helps,

best wishes,
Jan-Mathijs


On 31 Jul 2025, at 17:03, cxd425--- via fieldtrip <fieldtrip at science.ru.nl> wrote:

Hi FieldTrip community,

I hope you’re doing well.

I was just curious how the p-values are computed at the first level - I couldn’t find any documentation explaining the behaviour of stat.prob when cfg.computeprob is set to true or false. When I set computeprob = false, the resulting stat object still contains p-values. Could it be that when cfg.computeprob = true, the p-values at the first level are computed using a permutation test, whereas when it’s set to false, a simpler non-permutation statistical test (e.g., a two-sample t-test) is used instead?

Any clarification would be greatly appreciated.

Best regards,
Cihan

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