Package: targeted 0.6

targeted: Targeted Inference

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>).

Authors:Klaus K. Holst [aut, cre], Benedikt Sommer [aut], Andreas Nordland [aut]

targeted_0.6.tar.gz
targeted_0.6.zip(r-4.5)targeted_0.6.zip(r-4.4)targeted_0.6.zip(r-4.3)
targeted_0.6.tgz(r-4.4-x86_64)targeted_0.6.tgz(r-4.4-arm64)targeted_0.6.tgz(r-4.3-x86_64)targeted_0.6.tgz(r-4.3-arm64)
targeted_0.6.tar.gz(r-4.5-noble)targeted_0.6.tar.gz(r-4.4-noble)
targeted_0.6.tgz(r-4.4-emscripten)targeted_0.6.tgz(r-4.3-emscripten)
targeted.pdf |targeted.html✨
targeted/json (API)
NEWS

# Install 'targeted' in R:

install.packages('targeted', repos = c('https://kkholst.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kkholst/targeted/issues

Pkgdown site:https://kkholst.github.io

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

causal-inference double-robust estimation semiparametric-estimation statistics openblas cpp openmp

6.86 score 10 stars 1 packages 30 scripts 751 downloads 46 exports 27 dependencies

Last updated 9 days agofrom:c8f5d1dc19. Checks:1 OK, 1 NOTE, 7 FAILURE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Jan 21 2025
R-4.5-win-x86_64	OUTDATED	Dec 25 2024
R-4.5-linux-x86_64	NOTE	Jan 21 2025
R-4.4-win-x86_64	OUTDATED	Dec 25 2024
R-4.4-mac-x86_64	OUTDATED	Dec 25 2024
R-4.4-mac-aarch64	OUTDATED	Dec 25 2024
R-4.3-win-x86_64	OUTDATED	Dec 25 2024
R-4.3-mac-x86_64	OUTDATED	Dec 25 2024
R-4.3-mac-aarch64	OUTDATED	Dec 25 2024

Exports:aipw alean ate calibrate calibration cate cate_link crr cv design estimate_truncatedscore expand.list isoregw ML ml_model NB NB2 nondom offsets pava predictor predictor_gam predictor_glm predictor_glmnet predictor_grf predictor_grf_binary predictor_hal predictor_isoreg predictor_sl predictor_xgboost predictor_xgboost_binary predictor_xgboost_count predictor_xgboost_cox predictor_xgboost_multiclass RATE RATE.surv riskreg riskreg_cens riskreg_fit riskreg_mle scoring SL softmax solve_ode specials specify_ode

Dependencies:cli codetools data.table digest future future.apply globals lattice lava listenv Matrix mets mvtnorm nloptr nnls numDeriv optimx parallelly pracma progressr R6 Rcpp RcppArmadillo rlang SQUAREM survival timereg

Average Treatment Effects

Klaus Kähler Holst

Rendered fromate.Rmdusingknitr::rmarkdownon Jan 21 2025.

Last update: 2025-01-21
Started: 2025-01-21

Conditional Average Treatment Effects (cate)

Klaus Kähler Holst

Rendered fromcate.Rmdusingknitr::rmarkdownon Jan 21 2025.

Last update: 2025-01-21
Started: 2025-01-21

Estimating a relative risk or risk difference with a binary exposure

Klaus Kähler Holst

Rendered fromriskregression.Rmdusingknitr::rmarkdownon Jan 21 2025.

Last update: 2025-01-21
Started: 2025-01-21

targeted::ode_solve: Solving Ordinary Differential Equations

Klaus Kähler Holst

Rendered fromode.Rmdusingknitr::rmarkdownon Jan 21 2025.

Last update: 2025-01-21
Started: 2025-01-21

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
AIPW estimator	aipw
Assumption Lean inference for generalized linear model parameters	alean
AIPW (doubly-robust) estimator for Average Treatement Effect	ate
Calibration (training)	calibrate calibration
calibration class object	calibration-class
Conditional Average Treatment Effect estimation	cate
Conditional Relative Risk estimation	cate_link
cross_validated class object	cross_validated cross_validated-class
Conditional Relative Risk estimation	crr
Cross-validation	cv
Extract design matrix	design
Estimation of mean clinical outcome truncated by event process	estimate_truncatedscore
Create a list from all combination of input variables	expand.list
ML model	ML
R6 class for prediction models	ml_model predictor predictor_gam predictor_glm predictor_glmnet predictor_grf predictor_grf_binary predictor_hal predictor_isoreg predictor_xgboost predictor_xgboost_binary predictor_xgboost_count predictor_xgboost_cox predictor_xgboost_multiclass
Naive Bayes	NB NB2
NB class object	NB-class
Find non-dominated points of a set	nondom
Pooled Adjacent Violators Algorithm	isoreg isoregw pava
Prediction for kernel density estimates	predict.density
Predictions for Naive Bayes Classifier	predict.NB
Superlearner (stacked/ensemble learner)	predictor_sl superlearner
Responder Average Treatment Effect	RATE
Responder Average Treatment Effect	RATE.surv
Risk regression	riskreg riskreg_fit riskreg_mle
Binary regression models with right censored outcomes	riskreg_cens
Predictive model scoring	scoring
SuperLearner wrapper for ml_model	SL
Softmax transformation	softmax
Solve ODE	solve_ode
Extract model component from design object	offsets offsets.design specials specials.design weights.design
Specify Ordinary Differential Equation (ODE)	specify_ode
targeted class object	ate.targeted riskreg.targeted targeted-class
Signed intersection Wald test	test_intersectsignedwald

Package: targeted 0.6

targeted: Targeted Inference

Average Treatment Effects

Conditional Average Treatment Effects (cate)

Estimating a relative risk or risk difference with a binary exposure

targeted::ode_solve: Solving Ordinary Differential Equations

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)