Package: TxEffectsSurvival 1.0.2

TxEffectsSurvival: Treatment Effect Inference for Terminal and Non-Terminal Events under Competing Risks

Provides several confidence interval and testing procedures, based on either semiparametric (using event-specific win ratios) or nonparametric measures, including the ratio of integrated cumulative hazard (RICH) and the ratio of integrated transformed cumulative hazard (RITCH), for treatment effect inference with terminal and non-terminal events under competing risks. The semiparametric results were developed in Yang et al. (2022 <doi:10.1002/sim.9266>), and the nonparametric results were developed in Yang (2025 <doi:10.1002/sim.70205>). For comparison, results for the win ratio (Finkelstein and Schoenfeld 1999 <doi:10.1002/(SICI)1097-0258(19990615)18:11%3C1341::AID-SIM129%3E3.0.CO;2-7>), Pocock et al. 2012 <doi:10.1093/eurheartj/ehr352>, and Bebu and Lachin 2016 <doi:10.1093/biostatistics/kxv032>) are included. The package also supports univariate survival analysis with a single event. In this package, effect size estimates and confidence intervals are obtained for each event type, and several testing procedures are implemented for the global null hypothesis of no treatment effect on either terminal or non-terminal events. Furthermore, a test of proportional hazards assumptions, under which the event-specific win ratios converge to hazard ratios, and a test of equal hazard ratios, are provided. For summarizing the treatment effect across all events, confidence intervals for linear combinations of the event-specific win ratios, RICH, or RITCH are available using pre-determined or data-driven weights. Asymptotic properties of these inference procedures are discussed in Yang et al. (2022 <doi:10.1002/sim.9266>) and Yang (2025 <doi:10.1002/sim.70205>).

Authors:Daewoo Pak [aut, cre], Song Yang [aut]

TxEffectsSurvival_1.0.2.tar.gz
TxEffectsSurvival_1.0.2.zip(r-4.7-any)TxEffectsSurvival_1.0.2.zip(r-4.6-any)TxEffectsSurvival_1.0.2.zip(r-4.5-any)
TxEffectsSurvival_1.0.2.tgz(r-4.6-any)TxEffectsSurvival_1.0.2.tgz(r-4.5-any)
TxEffectsSurvival_1.0.2.tar.gz(r-4.7-any)TxEffectsSurvival_1.0.2.tar.gz(r-4.6-any)
TxEffectsSurvival_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TxEffectsSurvival/json (API)

# Install 'TxEffectsSurvival' in R:
install.packages('TxEffectsSurvival', repos = c('https://daewoopak.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • colon_wr - Colon cancer trial example data (Obs vs Lev+5FU) for semi-competing risks analyses

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 1 scripts 279 downloads 12 exports 0 dependencies

Last updated from:6c48a7844b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK88
source / vignettesOK123
linux-releaseOK88
macos-releaseOK96
macos-oldrelOK90
windows-develOK62
windows-releaseOK59
windows-oldrelOK67
wasm-releaseOK63

Exports:fn_dsfn_ginffn_glinsimfn_gmhatfn_logrankfn_pvalfn_solvefn_tntinffn_wr0print.tnt.analysistnt.analysistnt.analysis.default

Dependencies: