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transportr: Transporting Intervention Effects from One Population to Another

Doubly-robust, non-parametric estimators for the transported average treatment effect from Rudolph, Williams, Stuart, and Diaz (2023) <doi:10.48550/arXiv.2304.00117> and the intent-to-treatment average treatment effect from Rudolph and van der Laan (2017) <doi:10.1111/rssb.12213>. Estimators are fit using cross-fitting and nuisance parameters are estimated using the Super Learner algorithm.

Version: 0.1.0
Imports: checkmate, cli, generics, ife, mlr3superlearner, origami, R6
Suggests: ranger, testthat (≥ 3.0.0)
Published: 2025-02-20
DOI: 10.32614/CRAN.package.transportr
Author: Nicholas Williams ORCID iD [aut, cre, cph], Kara Rudolph ORCID iD [aut, cph]
Maintainer: Nicholas Williams <ntwilliams.personal at gmail.com>
BugReports: https://github.com/nt-williams/transportr/issues
License: GPL (≥ 3)
URL: https://github.com/nt-williams/transportr
NeedsCompilation: no
Materials: README NEWS
CRAN checks: transportr results

Documentation:

Reference manual: transportr.pdf

Downloads:

Package source: transportr_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: transportr_0.1.0.zip
macOS binaries: r-devel (arm64): transportr_0.1.0.tgz, r-release (arm64): transportr_0.1.0.tgz, r-oldrel (arm64): transportr_0.1.0.tgz, r-devel (x86_64): transportr_0.1.0.tgz, r-release (x86_64): transportr_0.1.0.tgz, r-oldrel (x86_64): transportr_0.1.0.tgz

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.