Introduction | Installation | Simulated Data | Backward Selection with AIC | Forward Selection with AIC | Different Selection Criteria | Forcing Variables with scope.min | Factor Variables | Interaction Terms | Polynomial Terms | Polynomial-Factor Interactions | Log Transformations | Three-Way Interactions | Full CRR Object | Missing Data | Using Subset | Best Practices | Troubleshooting | References | Session Info
Package: crrstep 2025.1.1
crrstep: Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model
Performs forward and backward stepwise regression for the proportional subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection criteria. BICcr has a penalty of k = log(n*), where n* is the number of primary events. This version includes improved handling of factors, interactions, and polynomial terms.
Authors:
crrstep_2025.1.1.tar.gz
crrstep_2025.1.1.zip(r-4.7)crrstep_2025.1.1.zip(r-4.6)crrstep_2025.1.1.zip(r-4.5)
crrstep_2025.1.1.tgz(r-4.6-any)crrstep_2025.1.1.tgz(r-4.5-any)
crrstep_2025.1.1.tar.gz(r-4.7-any)crrstep_2025.1.1.tar.gz(r-4.6-any)
crrstep_2025.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
crrstep/json (API)
| # Install 'crrstep' in R: |
| install.packages('crrstep', repos = c('https://rvaradhan.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:16bea5802d. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 109 | ||
| source / vignettes | OK | 173 | ||
| linux-release-x86_64 | OK | 128 | ||
| macos-release-arm64 | OK | 81 | ||
| macos-oldrel-arm64 | OK | 94 | ||
| windows-devel | OK | 89 | ||
| windows-release | OK | 91 | ||
| windows-oldrel | OK | 96 | ||
| wasm-release | OK | 95 |
Exports:crrstep
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Stepwise regression procedure for the Fine & Gray regression model in competing risks | crrstep-package |
| Stepwise Regression for Fine-Gray Competing Risks Model | AIC.crrstep BIC.crrstep coef.crrstep confint.crrstep crrstep logLik.crrstep print.crrstep print.summary.crrstep summary.crrstep vcov.crrstep |
