nimare.meta.ibma.Stouffers

class Stouffers(inference='ffx', null='theoretical', n_iters=None, two_sided=True, *args, **kwargs)

A t-test on z-statistic images. Requires z-statistic images.

Parameters:

• inference ({'ffx', 'rfx'}, optional) – Whether to use fixed-effects inference (default) or random-effects inference.
• null ({'theoretical', 'empirical'}, optional) – Whether to use a theoretical null T distribution or an empirically- derived null distribution determined via sign flipping. Empirical null is only possible if inference = 'rfx'.
• n_iters (int or None, optional) – The number of iterations to run in estimating the null distribution. Only used if inference = 'rfx' and null = 'empirical'.
• two_sided (bool, optional) – Whether to do a two- or one-sided test. Default is True.

Methods

fit(self, dataset)	Fit Estimator to Dataset.
get_params(self[, deep])	Get parameters for this estimator.
load(filename[, compressed])	Load a pickled class instance from file.
save(self, filename[, compress])	Pickle the class instance to the provided file.
set_params(self, \*\*params)	Set the parameters of this estimator.

fit(self, dataset)

Fit Estimator to Dataset.

Parameters:dataset (nimare.dataset.Dataset) – Dataset object to analyze. Returns:Results of Estimator fitting. Return type:nimare.base.base.MetaResult

get_params(self, deep=True)

Get parameters for this estimator.

Parameters:deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators. Returns:params – Parameter names mapped to their values. Return type:mapping of string to any

classmethod load(filename, compressed=True)

Load a pickled class instance from file.

Parameters:

• filename (str) – Name of file containing object.
• compressed (bool, optional) – If True, the file is assumed to be compressed and gzip will be used to load it. Otherwise, it will assume that the file is not compressed. Default = True.

Returns:

obj – Loaded class object.

Return type:

class object

save(self, filename, compress=True)

Pickle the class instance to the provided file.

Parameters:

• filename (str) – File to which object will be saved.
• compress (bool, optional) – If True, the file will be compressed with gzip. Otherwise, the uncompressed version will be saved. Default = True.

set_params(self, **params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Returns: Return type:self