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coxphf: Cox Regression with Firth's Penalized Likelihood

Implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see Heinze and Schemper (2001) and Heinze and Dunkler (2008). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals.

Version: 1.13.4
Depends: R (≥ 3.5.0)
Imports: survival, generics, tibble
Published: 2023-08-11
DOI: 10.32614/CRAN.package.coxphf
Author: Georg Heinze [aut, cre], Meinhard Ploner [aut], Lena Jiricka [aut], Gregor Steiner [aut]
Maintainer: Georg Heinze <georg.heinze at meduniwien.ac.at>
BugReports: https://github.com/georgheinze/coxphf/issues/
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://cemsiis.meduniwien.ac.at/kb/wf/software/statistische-software/fccoxphf/
NeedsCompilation: yes
Materials: README
In views: Survival
CRAN checks: coxphf results

Documentation:

Reference manual: coxphf.pdf

Downloads:

Package source: coxphf_1.13.4.tar.gz
Windows binaries: r-devel: coxphf_1.13.4.zip, r-release: coxphf_1.13.4.zip, r-oldrel: coxphf_1.13.4.zip
macOS binaries: r-release (arm64): coxphf_1.13.4.tgz, r-oldrel (arm64): coxphf_1.13.4.tgz, r-release (x86_64): coxphf_1.13.4.tgz, r-oldrel (x86_64): coxphf_1.13.4.tgz
Old sources: coxphf archive

Reverse dependencies:

Reverse depends: PHInfiniteEstimates

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.