ciccr: Causal Inference in Case-Control and Case-Population Studies

Estimation and inference methods for causal relative and attributable risk in case-control and case-population studies under the monotone treatment response and monotone treatment selection assumptions. For more details, see the paper by Jun and Lee (2023), "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," <doi:10.48550/arXiv.2004.08318>, accepted for publication in Journal of Business & Economic Statistics.

Version:	0.3.0
Depends:	R (≥ 2.10)
Imports:	stats, glmnet
Suggests:	knitr, rmarkdown, testthat, MASS, splines, Matrix
Published:	2023-10-20
DOI:	10.32614/CRAN.package.ciccr
Author:	Sung Jae Jun [aut], Sokbae Lee [aut, cre]
Maintainer:	Sokbae Lee <sl3841 at columbia.edu>
BugReports:	https://github.com/sokbae/ciccr/issues
License:	GPL-3
URL:	https://github.com/sokbae/ciccr/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	ciccr results

Documentation:

Reference manual:	ciccr.pdf
Vignettes:	Causal Inference in Case-Control and Case-Population Studies: Vignette

Downloads:

Package source:	ciccr_0.3.0.tar.gz
Windows binaries:	r-devel: ciccr_0.3.0.zip, r-release: ciccr_0.3.0.zip, r-oldrel: ciccr_0.3.0.zip
macOS binaries:	r-release (arm64): ciccr_0.3.0.tgz, r-oldrel (arm64): ciccr_0.3.0.tgz, r-release (x86_64): ciccr_0.3.0.tgz, r-oldrel (x86_64): ciccr_0.3.0.tgz
Old sources:	ciccr archive

Linking:

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