Discriminability for a multivariate measure (64k vertices)
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Description
Hi there,
I've got a measure of shape (subjects, sessions, vertices). That is, the measure consists of multiple values per session per subject. The input shape required by hyppo.discrim.DiscrimOneSample is (subjects, sessions) which implies a univariate measure per session, as far as I understood it. What would you recommend to circumvent this?
Also, it would be useful if code examples in the documentation involved data resembling real data (e.g. fMRI, connectivity) and an example of a research question concerning reproducibility assessment.
Thanks in advance
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start with hyppo.discrim.DiscrimOneSample and its documented (subjects, sessions) input shape. Determine how a (subjects, sessions, vertices) measure should be handled, and define what recommendation or supported behavior would address the question. Also review the documentation examples so they use realistic fMRI or connectivity data and include a reproducibility-assessment question.
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Assessment
- Tech stack
- python
- Domain
- data, documentation
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100