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drtmle: Doubly-Robust Nonparametric Estimation and Inference

Targeted minimum loss-based estimators of counterfactual means and causal effects that are doubly-robust with respect both to consistency and asymptotic normality (Benkeser et al (2017), <doi:10.1093/biomet/asx053>; MJ van der Laan (2014), <doi:10.1515/ijb-2012-0038>).

Version: 1.1.2
Depends: R (≥ 3.5.0)
Imports: SuperLearner, np, future.apply
Suggests: testthat, knitr, rmarkdown, gam, quadprog, nloptr, parallel, foreach, stringi
Published: 2023-01-05
DOI: 10.32614/CRAN.package.drtmle
Author: David Benkeser ORCID iD [aut, cre, cph], Nima Hejazi ORCID iD [ctb]
Maintainer: David Benkeser <benkeser at emory.edu>
BugReports: https://github.com/benkeser/drtmle/issues
License: MIT + file LICENSE
URL: https://github.com/benkeser/drtmle
NeedsCompilation: no
Materials: NEWS
In views: CausalInference
CRAN checks: drtmle results

Documentation:

Reference manual: drtmle.pdf
Vignettes: 'drtmle': Doubly-Robust Inference in R

Downloads:

Package source: drtmle_1.1.2.tar.gz
Windows binaries: r-devel: drtmle_1.1.2.zip, r-release: drtmle_1.1.2.zip, r-oldrel: drtmle_1.1.2.zip
macOS binaries: r-release (arm64): drtmle_1.1.2.tgz, r-oldrel (arm64): drtmle_1.1.2.tgz, r-release (x86_64): drtmle_1.1.2.tgz, r-oldrel (x86_64): drtmle_1.1.2.tgz
Old sources: drtmle archive

Reverse dependencies:

Reverse imports: biotmle

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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