[Neuroimaging] Performing voxel wise logistic regression
sulantha.s at gmail.com
Tue Nov 24 17:43:32 EST 2015
C is a categorial variable. I think logistic regression is what I am looking for. Thank you very much.
> On Nov 24, 2015, at 5:38 PM, bthirion <bertrand.thirion at inria.fr> wrote:
> Dear Sulantha,
> I'm not sure I understand your question: do you mean that C is a (categorical) scalar value (e.g. disease status of the patient or some task index), or C is also a volume ?
> I guess that C is a scalar, and that you're in fact running some kind of multivariate analysis. You may want to take a look at the following example: nilearn.github.io/auto_examples/decoding/plot_haxby_anova_svm.html#example-decoding-plot-haxby-anova-svm-py (just replace the SVM with a logistic regression).
> Regarding the interaction term, we don't have implementation for that AFAIK, but this is really straightforward to do with numpy pointwise mulitplication of arrays after applying the NiftiMasker.
> On 24/11/2015 23:27, Sulantha Sanjeewa wrote:
>> Hello all,
>> I would like to know whether it is possible to perform voxel wise logistic regression with two volumetric regressors (with an interaction term) using Nipy.
>> C ~ A + B + A*B
>> Where, C is either 1 or 0,
>> A and B both volumetric data.
>> Thank you very much.
>> Neuroimaging mailing list
>> Neuroimaging at python.org <mailto:Neuroimaging at python.org>
>> https://mail.python.org/mailman/listinfo/neuroimaging <https://mail.python.org/mailman/listinfo/neuroimaging>
> Neuroimaging mailing list
> Neuroimaging at python.org
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the Neuroimaging