Package: medoutcon 0.2.2

medoutcon: Efficient Natural and Interventional Causal Mediation Analysis

Efficient estimators of interventional (in)direct effects in the presence of mediator-outcome confounding affected by exposure. The effects estimated allow for the impact of the exposure on the outcome through a direct path to be disentangled from that through mediators, even in the presence of intermediate confounders that complicate such a relationship. Currently supported are non-parametric efficient one-step and targeted minimum loss estimators based on the formulation of Díaz, Hejazi, Rudolph, and van der Laan (2020) <doi:10.1093/biomet/asaa085>. Support for efficient estimation of the natural (in)direct effects is also provided, appropriate for settings in which intermediate confounders are absent. The package also supports estimation of these effects when the mediators are measured using outcome-dependent two-phase sampling designs (e.g., case-cohort).

Authors:Nima Hejazi [aut, cre, cph], Iván Díaz [aut], Kara Rudolph [aut], Philippe Boileau [ctb], Mark van der Laan [ctb, ths]

medoutcon_0.2.2.tar.gz
medoutcon_0.2.2.zip(r-4.5)medoutcon_0.2.2.zip(r-4.4)medoutcon_0.2.2.zip(r-4.3)
medoutcon_0.2.2.tgz(r-4.5-any)medoutcon_0.2.2.tgz(r-4.4-any)medoutcon_0.2.2.tgz(r-4.3-any)
medoutcon_0.2.2.tar.gz(r-4.5-noble)medoutcon_0.2.2.tar.gz(r-4.4-noble)
medoutcon_0.2.2.tgz(r-4.4-emscripten)medoutcon_0.2.2.tgz(r-4.3-emscripten)
medoutcon.pdf |medoutcon.html
medoutcon/json (API)
NEWS

# Install 'medoutcon' in R:
install.packages('medoutcon', repos = c('https://nhejazi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nhejazi/medoutcon/issues

On CRAN:

Conda:

causal-inferencecausal-machine-learninginverse-probability-weightsmachine-learningmediation-analysisstochastic-interventionstargeted-learningtreatment-effects

4.46 score 13 stars 22 scripts 1 exports 125 dependencies

Last updated 1 years agofrom:e2d3fd8a64. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 19 2025
R-4.5-winOKFeb 19 2025
R-4.5-macOKFeb 19 2025
R-4.5-linuxOKFeb 19 2025
R-4.4-winOKFeb 19 2025
R-4.4-macOKFeb 19 2025
R-4.3-winOKFeb 19 2025
R-4.3-macOKFeb 19 2025

Exports:medoutcon

Dependencies:abindassertthatbackportsbase64encBBmiscbitopsbslibcachemcaretcaToolscheckmateclasscliclockcodetoolscolorspacecpp11crayondata.tabledelayeddiagramdigestdplyre1071evaluatefansifarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2glm2globalsgluegowergplotsgtablegtoolshardhathighrhmshtmltoolshtmlwidgetsigraphipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimeModelMetricsmunsellnlmennetnumDerivorigamiparallellypillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRdpackrecipesreshape2rlangrmarkdownROCRrpartrstackdequesassscalesshapesl3sparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8uuidvctrsviridisLitevisNetworkwithrxfunyamlzeallot

Efficient causal mediation analysis with the natural and interventional effects

Rendered fromintro_medoutcon.Rmdusingknitr::rmarkdownon Feb 19 2025.

Last update: 2024-03-04
Started: 2019-04-07