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," <arXiv:2004.08318 [econ.EM]>, 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
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
Old sources: ciccr archive

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