[pymvpa] group level test on decoding accuracy
jinjingwen111 at gmail.com
Mon May 11 12:49:28 UTC 2015
Thanks Michael for this information! Definitely good to know and I will try
On Sun, May 10, 2015 at 9:40 AM, Michael Hanke <michael.hanke at gmail.com>
> FYI: the stelzer algorith is now available in PyMVPA.
> On May 10, 2015 14:28, "Christopher J Markiewicz" <effigies at bu.edu> wrote:
>> On 05/09/2015 12:49 PM, Jingwen Jin wrote:
>> > Hi MVPA experts,
>> > I have a general question about conducting group-level analysis on the
>> > subjects' classification accuracy maps. Let's say I am doing a
>> > one-sample t-test to find the voxels that have high classification
>> > accuracy across subjects. Essentially, I am doing a t-test on percentage
>> > numbers (SVM classification accuracy measured as percentage correct).
>> > Since percentage is highly affected by the testing example numbers, and
>> > in general would probably not meet the normal distribution assumption
>> > for t-test.
>> > So my question is if people adjust for testing trial numbers or any sort
>> > of transformation? For example, I converted each voxel's percentage
>> > number to a z score at the individual subject's classification map
>> > level, and then do group-level t-test on these z score maps. I wonder if
>> > this is valid?
>> What you describe sounds like the strategy used by Lee et al (2012)
>> <https://dx.doi.org/10.1523/JNEUROSCI.3814-11.2012> so there's
>> precedent. On the other hand, it's not clear to me how to do cluster
>> thresholding for multiple comparisons correction properly, using this
>> method. They use SPM8's random effects analysis, but if I recall
>> correctly that requires smoothness assumptions, while MVPA analyses
>> typically use unsmoothed volumes.
>> There's also a much more intensive non-parametric test used by Stelzer
>> et al. (2012) <https://dx.doi.org/10.1016/j.neuroimage.2012.09.063>, but
>> it requires a lot of computing time and at least temporary storage space.
>> Christopher J Markiewicz
>> Ph.D. Candidate, Quantitative Neuroscience Laboratory
>> Boston University
>> Pkg-ExpPsy-PyMVPA mailing list
>> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
> Pkg-ExpPsy-PyMVPA mailing list
> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
Jingwen Frances Jin
Department of Psychology
Stony Brook University
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