Package: ciccr 0.3.0

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.

Authors:Sung Jae Jun [aut], Sokbae Lee [aut, cre]

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ciccr.pdf |ciccr.html✨
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NEWS

# Install 'ciccr' in R:
install.packages('ciccr', repos = c('https://sokbae.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sokbae/ciccr/issues

Datasets:

On CRAN:

case-control-studiescausal-inferencepartial-identificationtreatment-effects

4.00 score 2 stars 4 scripts 203 downloads 7 exports 10 dependencies

Last updated 1 years agofrom:6941495efe. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-winOKNov 14 2024
R-4.5-linuxOKNov 14 2024
R-4.4-winOKNov 14 2024
R-4.4-macOKNov 14 2024
R-4.3-winOKNov 14 2024
R-4.3-macOKNov 14 2024

Exports:AAA_DMLavg_AR_logitavg_RR_logitcicc_ARcicc_plotcicc_RRtrim_pr

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival

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

Rendered fromciccr-vignette.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-10-20
Started: 2020-08-02