Dear SPM users,
in a recent VBM paper by Melzer and colleagues (2012, Neuroimage) different smoothing kernels were evaluated by calculating the percentage of voxels with non-normal distribution of the residuals using the toolbox SPMd by Luo and Nichols (2003, Neuroimage). I recently tried the same with some VBM data. The toolbox itself works fine, but I'm wondering how to calculate the number of voxels that violate the assumptions in an easy way.
In an SPMd tutorial ( http://www.google.de/url?sa=t&rct=j&q=spmd%20tutorial&source=web&cd=1&ved=0CEkQFjAA&url=http%3A%2F%2F128.196.98.224%2FPublic%2FImaging%2FSPM%2FFaceHouse%2FDocs%2FSPMd_Tutorial.doc&ei=NJwiUNimGdHmtQbC4IGABw&usg=AFQjCNGgSJpN9bsuCJNrSYE2cNw8EKo_vg&cad=rja ) I came across the following:
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Img_nltFrac.m and spmdbatch.m
Img_nltFrac.m is not part of spmd, but was written by Thomas Nichols.
Img_nltFrac calculates the proportion of voxels that violate the assumptions of the test, given a particular (uncorrected) p-value.
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Are these scripts available somewhere?
Thanks for any comments!
Gabor
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