causalCmprsk: Nonparametric and Cox-Based Estimation of ATE in Competing Risks

Estimation of average treatment effects (ATE) of two static treatment regimes on time-to-event outcomes with K competing events (K can be 1). The method uses propensity scores weighting for emulation of baseline randomization.

Version: 1.0.3
Depends: R (≥ 3.6)
Imports: survival, inline, doParallel, parallel, utils, foreach, data.table, purrr
Suggests: knitr, rmarkdown, bookdown, tidyverse, ggalt, cobalt, ggsci, modEvA, naniar, DT, Hmisc, hrbrthemes, summarytools, kableExtra
Published: 2021-08-09
Author: Bella Vakulenko-Lagun, Colin Magdamo, Marie-Laure Charpignon, Bang Zheng, Mark Albers, Sudeshna Das
Maintainer: Bella Vakulenko-Lagun <blagun at stat.haifa.ac.il>
BugReports: https://github.com/Bella2001/causalCmprsk/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/Bella2001/causalCmprsk
NeedsCompilation: no
Materials: README
CRAN checks: causalCmprsk results

Documentation:

Reference manual: causalCmprsk.pdf
Vignettes: Nonparametric and Cox-based estimation of ATE in competing risks

Downloads:

Package source: causalCmprsk_1.0.3.tar.gz
Windows binaries: r-devel: causalCmprsk_1.0.3.zip, r-release: causalCmprsk_1.0.3.zip, r-oldrel: causalCmprsk_1.0.3.zip
macOS binaries: r-release (arm64): causalCmprsk_1.0.3.tgz, r-release (x86_64): causalCmprsk_1.0.3.tgz, r-oldrel: causalCmprsk_1.0.3.tgz
Old sources: causalCmprsk archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=causalCmprsk to link to this page.