causalCmprsk: Nonparametric and Cox-Based Estimation of Average Treatment Effects in Competing Risks

Estimation of average treatment effects (ATE) of point interventions on time-to-event outcomes with K competing risks (K can be 1). The method uses propensity scores and inverse probability weighting for emulation of baseline randomization, which is described in Charpignon et al. (2022) <doi:10.1038/s41467-022-35157-w>.

Version:	2.0.0
Depends:	R (≥ 4.0.0)
Imports:	survival, inline, doParallel, parallel, utils, foreach, data.table, purrr, methods
Suggests:	knitr, rmarkdown, bookdown, tidyverse, ggalt, cobalt, ggsci, modEvA, naniar, DT, Hmisc, hrbrthemes, summarytools
Published:	2023-07-04
DOI:	10.32614/CRAN.package.causalCmprsk
Author:	Bella Vakulenko-Lagun [aut, cre], Colin Magdamo [aut], Marie-Laure Charpignon [aut], Bang Zheng [aut], Mark Albers [aut], Sudeshna Das [aut]
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 average treatment effects in competing risks using 'causalCmprsk' package

Downloads:

Package source:	causalCmprsk_2.0.0.tar.gz
Windows binaries:	r-devel: causalCmprsk_2.0.0.zip, r-release: causalCmprsk_2.0.0.zip, r-oldrel: causalCmprsk_2.0.0.zip
macOS binaries:	r-release (arm64): causalCmprsk_2.0.0.tgz, r-oldrel (arm64): causalCmprsk_2.0.0.tgz, r-release (x86_64): causalCmprsk_2.0.0.tgz, r-oldrel (x86_64): causalCmprsk_2.0.0.tgz
Old sources:	causalCmprsk archive

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