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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
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:

Please use the canonical form https://CRAN.R-project.org/package=drtmle to link to this page.

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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