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add confidence interval output to paired DeLong test #95
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I'm not sure what the AppVeyor build failed check means or how to fix it :( |
Thanks for the code, that's really neat! The AppVeyor CI ensures everything is working properly and that the code can be submitted to CRAN. It runs 1.
This means you should update the documentation (in man/roc.test.Rd) to match the changes in the code. 2.The error hints at the following line in the test suite:
The test ensures that no output is produced. However now there's the following output:
Not sure how to fix that cleanly at the moment. Maybe we could default to 0.95? By the way, I would move the messages to roc.test. Other functions in delong.R don't check/fix their arguments. |
One comment about performance. The delong calculations are now performed twice, in:
Although it isn't obvious from the code, and the fact that the function is implemented in C++, the DeLong placements are still very expensive to compute, especially for larger ROC curves. Is it possible to change the code a bit to avoid re-computing everything? |
Yes it is possible, and I considered doing this--I think for the best fix, the shared code to be moved into another function which is called by both If it is refactored in this way I think that
I think checking the value of the conf.level argument inside of
Easy enough, hopefully :) |
Checks have passed with updated pull request (also refactors the paired DeLong test/CI calculations as described). |
Any updates on whether this can be approved? |
That's great thanks! I've been very busy these days and haven't really had much time to look into this, sorry about that. For the time being I think this can be merged in a feature branch. To release it / merge into master, I'd like to have the following:
Last thing, this isn't very fresh in my mind, so I might be wrong (I did that 10 years ago). The DeLong paper describes how to do a paired (correlated) test. But I remember it was reasonably easy to extend to unpaired curves. Do you have a feeling for how easily this could be done? This would keep the interface consistent between paired and unpaired... But I guess that's beyond this pull request. |
I can definitely fix the docs and test. (Sorry, I have no experience with package development so I didn't know this needed to be done.) Not sure about the unpaired CI extension--the paired CI is based on a pivot quantity which has a standard normal distribution. I think I can emulate the CI calculation for the unpaired test, but it's beyond my knowledge of mathematical statistics to know what distribution the adjusted pivot would have--from the code, I assume a |
That's awesome, thanks a lot! |
Addresses issue #73 for PAIRED TESTS only using the paper mentioned in the issue discussion.