[Neuroimaging] Performing voxel wise logistic regression

[Sulantha Sanjeewa]

Hi, 
C is a categorial variable. I think logistic regression is what I am looking for. Thank you very much. 
Best, 
S. 
> 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.
> 
>      Best,
> 
> Bertrand
> 
> 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. 
>> Model:
>> C ~ A + B + A*B
>> Where, C is either 1 or 0, 
>> A and B both volumetric data. 
>> Thank you very much. 
>> 
>> 
>> 
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