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URL: http://www.warwick.ac.uk/snpm
Proper Citation: Statistical non-Parametric Mapping (RRID:SCR_002092)
Description: A toolbox for Statistical Parametric Mapping (SPM) that provides an extensible framework for voxel level non-parametric permutation/randomization tests of functional Neuroimaging experiments with independent observations. SnPM uses the General Linear Model to construct pseudo t-statistic images, which are then assessed for significance using a standard non-parametric multiple comparisons procedure based on randomization/permutation testing. It is most suitable for single subject PET/SPECT analyses, or designs with low degrees of freedom available for variance estimation. In these situations the freedom to use weighted locally pooled variance estimates, or variance smoothing, makes the non-parametric approach considerably more powerful than conventional parametric approaches, as are implemented in SPM. Further, the non-parametric approach is always valid, given only minimal assumptions. The SnPM toolbox provides an alternative to the Statistics section of SPM.
Abbreviations: SnPM
Synonyms: SnPM: Statistical nonParametric Mapping, SnPM - Statistical NonParametric Mapping - A toolbox for SPM, Statistical nonParametric Mapping
Resource Type: software toolkit, software resource, data processing software, software application
Keywords: analyze, linear, linux, macos, matlab, microsoft, magnetic resonance, nifti, posix/unix-like, regression, statistical operation, sunos/solaris, windows, statistical parametric mapping, pet, spect
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