nimare.meta.ibma.FFX_GLM

class FFX_GLM(cdt=0.01, q=0.05, two_sided=True, *args, **kwargs)[source]

An image-based meta-analytic test using contrast and standard error images. Don’t estimate variance, just take from first level.

Parameters

  • cdt (float, optional) – Cluster-defining p-value threshold.

  • q (float, optional) – Alpha for multiple comparisons correction.

  • two_sided (bool, optional) – Whether analysis should be two-sided (True) or one-sided (False).

fit(dataset)[source]

Fit Estimator to Dataset.

Parameters

dataset (nimare.dataset.Dataset) – Dataset object to analyze.

Returns

nimare.results.MetaResult – Results of Estimator fitting.

Notes

The fit method is a light wrapper that runs input validation and preprocessing before fitting the actual model. Estimators’ individual “fitting” methods are implemented as _fit, although users should call fit.

get_params(deep=True)[source]

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 (mapping of string to any) – Parameter names mapped to their values.

classmethod load(filename, compressed=True)[source]

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 (class object) – Loaded class object.

save(filename, compress=True)[source]

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(**params)[source]

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

self