Implement (cause-specific) competing risks#782
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Extend survival forests to handle competing risks data where the status variable encodes censoring (0) or one of K event types (1, 2, ..., K). Uses composite sum of squared log-rank statistics across event types for splitting, following Ishwaran et al. (2014). Returns cause-specific CHFs as a list of K matrices and cumulative incidence functions (CIF) via the Aalen-Johansen estimator. Fully backward compatible when K=1. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- R/utility.R: prob -> probs in quantile() call - test_interface.R: dependent.variable -> dependent.variable.name - test_ranger.R: $prediction -> $predictions Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Update roxygen docs for ranger() and predict.ranger() with competing risks parameters, return values, and examples - Add Ishwaran et al. (2014) reference for cause-specific hazard approach - Add vignettes/competing_risks.Rmd with method description and usage - Add inst/examples/competing_risks_comparison.R (ranger vs rfsrc) - Add knitr/rmarkdown to Suggests and VignetteBuilder to DESCRIPTION Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Just an experiment to see how it goes when I point Claude Code at it 🤷🏻♂️