doi:10.1111/j.1541-0420.2005.00377.x>), variable importance and conditional average treatment effects (CATE) (van der Laan (2006) <doi:10.2202/1557-4679.1008>), estimators for risk differences and relative risks (Richardson et al. (2017) <doi:10.1080/01621459.2016.1192546>), assumption lean inference for generalized linear model parameters (Vansteelandt et al. (2022) <doi:10.1111/rssb.12504>).">

targeted: Targeted Inference (original) (raw)

Various methods for targeted and semiparametric inference including augmented inverse probability weighted (AIPW) estimators for missing data and causal inference (Bang and Robins (2005) <doi:10.1111/j.1541-0420.2005.00377.x>), variable importance and conditional average treatment effects (CATE) (van der Laan (2006) <doi:10.2202/1557-4679.1008>), estimators for risk differences and relative risks (Richardson et al. (2017) <doi:10.1080/01621459.2016.1192546>), assumption lean inference for generalized linear model parameters (Vansteelandt et al. (2022) <doi:10.1111/rssb.12504>).

Version: 0.5
Depends: R (≥ 4.0), lava (≥ 1.7.0)
Imports: data.table, digest, futile.logger, future.apply, optimx, progressr, methods, mets, R6, Rcpp (≥ 1.0.0), survival
LinkingTo: Rcpp, RcppArmadillo
Suggests: grf, mgcv, testthat (≥ 0.11), rmarkdown, scatterplot3d, SuperLearner (≥ 2.0-28), knitr, xgboost, viridisLite
Published: 2024-02-22
DOI: 10.32614/CRAN.package.targeted
Author: Klaus K. Holst [aut, cre], Andreas Nordland [aut]
Maintainer: Klaus K. Holst
BugReports: https://github.com/kkholst/targeted/issues
License: Apache License (== 2.0)
NeedsCompilation: yes
Materials: README NEWS
In views: MissingData
CRAN checks: targeted results

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Reverse imports: polle
Reverse suggests: lava

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