Hi, I've poked around a little more, and I'm wondering if L2 normalization would ameliorate my second issue regarding lesion size being a confounding factor in my classification? http://www.pymvpa.org/generated/mvpa.misc.transformers.l2_normed.html
At the end of the day, all I mainly want to ensure that (a) 0/1 scaling is correct and (b) determine how much of the CV is due to lesion size alone. If it were a simpler univariate regression, I could include lesion size as a covariate, but I'm not sure how to do something analogous in PyMVPA. Thanks! David On Sep 6, 2011, at 12:52 AM, David V. Smith wrote: > > Hello, > > I have lesion data, and I am trying to test whether particular patterns of > lesions distinguish two classes of patients. I have two questions: > > 1) What is the best way to scale the lesion data? Traditionally, these data > are represented with 1s (lesion) and 0s (no lesion). I've played around with > different scalings, and I've gotten different (but replicable) results using > the SMLR classifier in PyMVPA 0.4. See below: first column is the > leave-one-out CV; second column the value for the spared voxels; third column > is the value for the damaged voxels. > CV NoLesion Lesion > 83.571 000 001 > 75.000 001 002 > 77.143 002 004 > 81.429 100 200 > 81.429 200 400 > > 2.) What is the best way to control for a nuisance factor? I know there is an > additional variable (i.e., lesion volume) that can distinguish between my two > patient groups, so I would like the resulting CV and heavily weighted voxels > to be uncontaminated by this nuisance factor. Ideally, I would like to know > how much additional predictive power is gained over and above this nuisance > factor. > > Thanks, > David > > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
_______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
