nimare.meta.ibma
.Stouffers¶
-
class
Stouffers
(use_sample_size=False, *args, **kwargs)[source]¶ Bases:
nimare.base.MetaEstimator
A t-test on z-statistic images. Requires z-statistic images.
- Parameters
use_sample_size (
bool
, optional) – Whether to use sample sizes for weights (i.e., “weighted Stouffer’s”) or not. Default is False.
Notes
Requires
z
images and optionally the sample size metadata field.Warning
This method does not currently calculate p-values correctly. Do not use.
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
Stouffer, S. A., Suchman, E. A., DeVinney, L. C., Star, S. A., & Williams Jr, R. M. (1949). The American Soldier: Adjustment during army life. Studies in social psychology in World War II, vol. 1. https://psycnet.apa.org/record/1950-00790-000
Zaykin, D. V. (2011). Optimally weighted Z‐test is a powerful method for combining probabilities in meta‐analysis. Journal of evolutionary biology, 24(8), 1836-1841. https://doi.org/10.1111/j.1420-9101.2011.02297.x
See also
pymare.estimators.StoufferCombinationTest
The PyMARE estimator called by this class.
-
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 callfit
.