Package: targeted 0.8

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], Christian B. Pipper [ctb]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
targeted/json (API)

# 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/docs site:https://kkholst.github.io

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

truncatedscore - Scores truncated by death

On CRAN:

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

8.67 score 14 stars 1 packages 32 scripts 3.6k downloads 57 exports 24 dependencies

Last updated from:ff494f06a8. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	302
linux-devel-x86_64	OK	292
source / vignettes	OK	430
linux-release-arm64	OK	323
linux-release-x86_64	OK	344
macos-release-arm64	OK	271
macos-release-x86_64	OK	496
macos-oldrel-arm64	OK	343
macos-oldrel-x86_64	OK	558
windows-devel	OK	395
windows-release	OK	387
windows-oldrel	OK	344
wasm-release	OK	247

Exports:aipw alean ate calibrate calibration cate cate_link crr cumhaz cv design estimate estimate_truncatedscore expand.list IC isoregw learner learner_expand_grid learner_gam learner_glm learner_glmnet_cv learner_grf learner_hal learner_isoreg learner_mars learner_naivebayes learner_sl learner_stratify learner_surv_cox learner_surv_rf learner_svm learner_xgboost metalearner_discrete metalearner_nnls naivebayes nondom parameter pava RATE RATE.surv riskreg riskreg_cens riskreg_fit riskreg_mle score scoring sim SL softmax solve_ode specify_ode strata stratify superlearner Surv test_intersection_sw test_zmax_onesided

Dependencies:abind cli codetools digest future future.apply globals lattice lava listenv Matrix mets mvtnorm numDeriv parallelly progressr quadprog R6 Rcpp RcppArmadillo rlang SQUAREM survival timereg

Prediction models

Rendered frompredictionclass.qmdusingquarto::html

Last update: 2026-04-08
Started: 2025-11-26

Estimating a relative risk or risk difference with a binary exposure

Rendered fromriskregression.qmdusingquarto::html

Last update: 2025-11-26
Started: 2025-11-26

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 Treatment Effect	ate
Calibration (training)	calibrate calibration
calibration class object	calibration-class
Conditional Average Treatment Effect estimation	cate
Conditional Relative Risk estimation	cate_link
Construct a learner	constructor_shared
cross_validated class object	cross_validated cross_validated-class
Conditional Relative Risk estimation	crr
Predict the cumulative hazard/survival function for a survival model	cumhaz
Cross-validation	cv cv.default
Cross-validation for learner_sl	cv.learner_sl
Cast warning for deprecated function argument names	deprecate_arg_warn
Deprecated argument names	deprecated_argument_names
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
Fit survival nuisance models	fit_survival_models
Integral approximation of a time dependent function.	int_surv
R6 class for prediction models	learner
Construct learners from a grid of parameters	learner_expand_grid
Construct a learner	learner_gam
Construct a learner	learner_glm
Construct a learner	learner_glmnet_cv
Construct a learner	learner_grf
Construct a learner	learner_hal
Construct a learner	learner_isoreg
Construct a learner	learner_mars
Construct a learner	learner_naivebayes
Construct a learner	learner_sl
Construct stratified learner	learner_stratify
Construct a learner	learner_surv_cox
Construct a learner	learner_surv_rf
Construct a learner	learner_svm
Construct a learner	learner_xgboost
Naive Bayes classifier	naivebayes
naivebayes class object	naivebayes-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.naivebayes
Predict Method for superlearner Fits	predict.superlearner
Responder Average Treatment Effect	RATE
Responder Average Treatment Effect	RATE.surv
Calculate the right censoring augmentation integral	rcai
Risk regression	riskreg riskreg_fit riskreg_mle
Binary regression models with right censored outcomes	riskreg_cens
Extract average cross-validated score of individual learners	score.superlearner
Predictive model scoring	scoring
SuperLearner wrapper for learner	SL
Softmax transformation	softmax
Solve ODE	solve_ode
Specify Ordinary Differential Equation (ODE)	specify_ode
Identify Stratification Variables	stratify
Superlearner (stacked/ensemble learner)	metalearner_discrete metalearner_nnls superlearner
Treatment level estimating functions for survival outcomes under right censoring	survival_treatment_level_estfun
targeted class object	ate.targeted riskreg.targeted targeted-class
Extract model component from design object	terms.design
Signed Wald intersection test	test_intersection_sw
One-sided Zmax test	test_zmax_onesided
Scores truncated by death	truncatedscore
Extract ensemble weights	weights.superlearner