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drcarlate: Improving Estimation Efficiency in CAR with Imperfect Compliance

We provide a list of functions for replicating the results of the Monte Carlo simulations and empirical application of Jiang et al. (2022). In particular, we provide corresponding functions for generating the three types of random data described in this paper, as well as all the estimation strategies. Detailed information about the data generation process and estimation strategy can be found in Jiang et al. (2022) <doi:10.48550/arXiv.2201.13004>.

Version:1.2.0
Depends:R (≥ 2.10)
Imports:pracma,MASS,stringr,splus2R,glmnet, stats,purrr
Suggests:knitr,rmarkdown
Published:2023-06-12
DOI:10.32614/CRAN.package.drcarlate
Author:Liang Jiang [aut, cph], Oliver B. Linton [aut, cph], Haihan Tang [aut, cph], Yichong Zhang [aut, cph], Mingxin Zhang [cre]
Maintainer:Mingxin Zhang <21110680035 at m.fudan.edu.cn>
License:MIT + fileLICENSE
NeedsCompilation:no
Materials:README,NEWS
CRAN checks:drcarlate results

Documentation:

Reference manual:drcarlate.html ,drcarlate.pdf
Vignettes:Introduction to drcarlate (source,R code)

Downloads:

Package source: drcarlate_1.2.0.tar.gz
Windows binaries: r-devel:drcarlate_1.2.0.zip, r-release:drcarlate_1.2.0.zip, r-oldrel:drcarlate_1.2.0.zip
macOS binaries: r-release (arm64):drcarlate_1.2.0.tgz, r-oldrel (arm64):drcarlate_1.2.0.tgz, r-release (x86_64):drcarlate_1.2.0.tgz, r-oldrel (x86_64):drcarlate_1.2.0.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=drcarlateto link to this page.


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