Cumulative Incidence (Kaplan-Meier) for competing risks.

[mvlvrd]

Add non-parametric Cumulative Incidence (Kaplan-Meier) for competing risks. Tests included.

Checklist

• closes Add Kaplan-Meier estimator for competing risks. #490
• pytest passes
• tests are included
• code is well formatted
• documentation renders correctly

What does this implement/fix? Explain your changes
Implements cumulative incidence estimator for the competing risks case. Confidence Intervals are not implemented but are under development.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.23%. Comparing base (41a5200) to head (9fc899a).
Report is 65 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #491      +/-   ##
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+ Coverage   98.21%   98.23%   +0.02%     
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  Files          37       37              
  Lines        3521     3564      +43     
  Branches      464      472       +8     
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+ Hits         3458     3501      +43     
  Misses         30       30              
  Partials       33       33              

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[mvlvrd]

The codacy linter triggers for unused unpacked assignments, however the ruff linter doesn't. Perhaps it would be nice to make them consistent, though is not a big issue. (I can open a new issue/PR if needed, it is trivial to fix it from the ruff side).

[sebp]

This is great, thanks a lot!

The code seems to be correct to me. I would suggest to improve the API docs a little bit to avoid ambiguities.

In addition, I'm not sure if certain corner cases are covered. For instance, what happens if no event has been observed for one (or more) competing risk?

I would appreciate if a test case with more than 2 competing risks could be added.

[mvlvrd]

Thanks so much for the review!
I think I have addressed most of your points. I have been looking for a real dataset with more than two risks, but I couldn't find one, so I added a simulated one. Corner cases like zero events for one (or more) particular risk are not included and raise an error.

I also changed the function name (removing the reference to Kaplan-Meier). This is because I found a couple of papers that use KM for the naive extension of KM to the competing risks case, while we are using the rigorous estimator that does not assume independence between risks.