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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: causalCmprsk results


Reference manual: causalCmprsk.pdf
Vignettes: Nonparametric and Cox-based estimation of average treatment effects in competing risks using 'causalCmprsk' package


Package source: causalCmprsk_2.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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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