nimare.workflows.cbma.PairwiseCBMAWorkflow
- PairwiseCBMAWorkflow(estimator=None, corrector=None, diagnostics=None, voxel_thresh=1.65, cluster_threshold=10, output_dir=None, n_cores=1)[source]
Base class for pairwise coordinate-based meta-analysis workflow methods.
Added in version 0.1.2.
- Parameters:
estimator (
PairwiseCBMAEstimator,str{‘alesubtraction’, ‘mkdachi2’}, or optional) – Meta-analysis estimator. Default isMKDAChi2.corrector (
Corrector,str{‘montecarlo’, ‘fdr’, ‘bonferroni’} or optional) – Meta-analysis corrector. Default isFWECorrector.diagnostics (
listofDiagnostics,Diagnostics,str{‘jackknife’, ‘focuscounter’}, or optional) – List of meta-analysis diagnostic classes. A single diagnostic class can also be passed. Default isFocusCounter.voxel_thresh (
floator None, optional) – An optional voxel-level threshold that may be applied to thetarget_imagein theDiagnosticsclass to define clusters. This can be None or 0 if thetarget_imageis already thresholded (e.g., a cluster-level corrected map). If diagnostics are passed as initialized objects, this parameter will be ignored. Default is 1.65, which corresponds to p-value = .05, one-tailed.cluster_threshold (
intor None, optional) – Cluster size threshold, in voxels. If None, then no cluster size threshold will be applied. If diagnostics are passed as initialized objects, this parameter will be ignored. Default is 10.output_dir (
str, optional) – Output directory in which to save results. If the directory doesn’t exist, it will be created. Default is None (the results are not saved).n_cores (
int, optional) – Number of cores to use for parallelization. If <=0, defaults to using all available cores. If estimator, corrector, or diagnostics are passed as initialized objects, this parameter will be ignored. Default is 1.