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ccwr: Clone-Censor-Weight Methods for Target Trial Emulation

Provides methods for clone-censor-weight analyses that emulate target trials with grace-period treatment strategies using observational time-to-event data. Tools clone participants across strategies, apply strategy-specific artificial censoring, and estimate inverse probability of censoring weights using pooled logistic or Cox models, fit weighted outcome models, and obtain subject-level bootstrap confidence intervals by repeating the complete analysis. The methods are described by Maringe et al. (2020) <doi:10.1093/ije/dyaa057> and Gaber et al. (2024) <doi:10.1002/cam4.70461>.

Version: 0.0.2
Depends: R (≥ 4.4.0)
Imports: dplyr, readr, survival, tibble, rlang, glue
Suggests: knitr, rmarkdown, testthat (≥ 3.2.0)
Published: 2026-09-03
DOI: 10.32614/CRAN.package.ccwr (may not be active yet)
Author: Sang Ho Park [aut, cre], Youngrok Lee [aut], Jihyeon Baek [aut], Hye Won Yang [aut], Donghoon Jeong [aut]
Maintainer: Sang Ho Park <shstat1729 at gmail.com>
BugReports: https://github.com/CausalInferenceLab/ccwr/issues
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS
ccwr copyright details
URL: https://github.com/CausalInferenceLab/ccwr
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: ccwr results

Documentation:

Reference manual: ccwr.html , ccwr.pdf
Vignettes: An Overview of the ccwr Package for R (source, R code)

Downloads:

Package source: ccwr_0.0.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): ccwr_0.0.2.tgz, r-oldrel (arm64): ccwr_0.0.2.tgz, r-release (x86_64): ccwr_0.0.2.tgz, r-oldrel (x86_64): ccwr_0.0.2.tgz

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.
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