pymare.results
.CombinationTestResults
- class CombinationTestResults(estimator, dataset, z=None, p=None)[source]
Bases:
object
Container for results generated by p-value combination methods.
- Parameters:
estimator (
BaseEstimator
) – The estimator used to produce the results.dataset (
Dataset
) – A Dataset instance containing the inputs to the estimator.z (
numpy.ndarray
, optional) – Array of z-scores. Default = None.p (
numpy.ndarray
, optional) – Array of right-tailed p-values. Default = None.
- property p
P-values.
- permutation_test(n_perm=1000)[source]
Run permutation test.
Warning
This method relies on the
.dataset
attribute, so the original Estimator must have be fitted withfit_dataset
, notfit
.- Parameters:
n_perm (
int
, optional) – Number of permutations to generate. The actual number used may be smaller in the event of an exact test (see below), but will never be larger. Default = 1000.- Returns:
An instance of class PermutationTestResults.
- Return type:
Notes
If the number of possible permutations is smaller than n_perm, an exact test will be conducted. Otherwise an approximate test will be conducted by randomly shuffling the outcomes n_perm times (or, for intercept-only models, by randomly flipping their signs). Permuted datasets are processed in parallel. This means that one can often set very high n_perm values (e.g., 100k) with little performance degradation.
- property z
Z-values.