Proposal to Include Working cmprsk.crr Learner in mlr3cmprsk #491
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Introduces LearnerCompRisksFineGrayCRR for Fine-Gray competing risks regression using the cmprsk package. Updates NAMESPACE to export the new learner, adds Andrzej Galecki as a contributor, and standardizes references in several learner documentation files to use format_bib. Documentation for the new learner is provided in mlr_learners_cmprsk.crr.Rd.
Introduces new test files for the cmprsk.crr learner, including autotests, parameter tests, and tests with different covariate configurations.
Introduces new test files for the cmprsk.crr learner, including autotest, pbc task emulation, covariate interaction, and parameter testing.
Added 'rlang' to the Suggests field in DESCRIPTION and included skip_if_not_installed('rlang') in relevant test files to ensure tests are skipped if rlang is not available. Also updated a call to explicitly use stats::contrasts for clarity.
Added the 'exclude = "utf8_feature_names"' argument to the run_autotest call in the crr learner test to skip tests related to UTF-8 feature names.
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Dear @agalecki, Your proposal makes sense - having Fine and Gray model in
We could also cross-check the code from tidycmprsk to see how they implement it there |
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Dear John,
I hope this finds you well—sorry if I'm catching up a bit late to yesterday's updates in mlr3proba.
My fork of mlr3extralearners includes a fully functional
cmprsk.crrlearner for the Fine-Gray competing risks model, designed for seamless integration into the package. It successfully passed all autotests prior to the recent changes inmlr3proba(from commit 05934fdef to dda033537 on GitHub), which unfortunately broke compatibility.Given the focus on competing risks in
mlr3cmprsk, I'd love to explore including this implementation there. It could provide immediate value for users handling Fine-Gray models. I'm happy to collaborate on any adjustments needed for alignment.What are your thoughts? Looking forward to hearing from you.
Best regards,
Andrzej