nimare.meta.ibma
.Stouffers
- class Stouffers(use_sample_size=False, **kwargs)[source]
Bases:
IBMAEstimator
A t-test on z-statistic images.
Requires z-statistic images.
This method is described in Stouffer et al.1.
- Parameters
use_sample_size (
bool
, optional) – Whether to use sample sizes for weights (i.e., “weighted Stouffer’s”) or not, as described in Zaykin2. Default is False.
Notes
Requires
z
images and optionally the sample size metadata field.fit()
produces aMetaResult
object with the following maps:“z”
Z-statistic map from one-sample test.
“p”
P-value map from one-sample test.
Warning
Masking approaches which average across voxels (e.g., NiftiLabelsMaskers) will result in invalid results. It cannot be used with these types of maskers.
All image-based meta-analysis estimators adopt an aggressive masking strategy, in which any voxels with a value of zero in any of the input maps will be removed from the analysis.
References
- 1
Samuel A Stouffer, Edward A Suchman, Leland C DeVinney, Shirley A Star, and Robin M Williams Jr. The american soldier: adjustment during army life.(studies in social psychology in world war ii), vol. 1. Studies in social psychology in World War II, 1949.
- 2
Dmitri V Zaykin. Optimally weighted z-test is a powerful method for combining probabilities in meta-analysis. Journal of evolutionary biology, 24(8):1836–1841, 2011. URL: https://doi.org/10.1111/j.1420-9101.2011.02297.x, doi:10.1111/j.1420-9101.2011.02297.x.
See also
pymare.estimators.StoufferCombinationTest
The PyMARE estimator called by this class.
Methods
fit
(dataset[, drop_invalid])Fit Estimator to Dataset.
get_params
([deep])Get parameters for this estimator.
load
(filename[, compressed])Load a pickled class instance from file.
save
(filename[, compress])Pickle the class instance to the provided file.
set_params
(**params)Set the parameters of this estimator.
- fit(dataset, drop_invalid=True)[source]
Fit Estimator to Dataset.
- Parameters
- Returns
Results of Estimator fitting.
- Return type
- Variables
inputs (
dict
) – Inputs used in _fit.
- classmethod load(filename, compressed=True)[source]
Load a pickled class instance from file.
- Parameters
- Returns
obj – Loaded class object.
- Return type
class object
- 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.- Return type
self