Package: medshift 0.1.4

Nima Hejazi

medshift: Causal mediation analysis for stochastic interventions

Estimators of a parameter arising in the decomposition of the population intervention (in)direct effect of stochastic interventions in causal mediation analysis, including efficient one-step, targeted minimum loss (TML), re-weighting (IPW), and substitution estimators. The parameter estimated constitutes a part of each of the population intervention (in)direct effects. These estimators may be used in assessing population intervention (in)direct effects under stochastic treatment regimes, including incremental propensity score interventions and modified treatment policies. The methodology was first discussed by I Díaz and NS Hejazi (2020) <doi:10.1111/rssb.12362>.

Authors:Nima Hejazi [aut, cre, cph], Iván Díaz [aut], Mark van der Laan [ctb, ths], Jeremy Coyle [ctb]

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medshift.pdf |medshift.html
medshift/json (API)

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

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

On CRAN:

Conda:

causal-inferenceinverse-probability-weightsmachine-learningmediation-analysisstochastic-interventionstargeted-learningtreatment-effects

3.73 score 9 stars 12 scripts 7 exports 125 dependencies

Last updated 3 years agofrom:0ae0572fc5. Checks:1 OK, 8 WARNING. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 28 2025
R-4.5-winWARNINGMar 28 2025
R-4.5-macWARNINGMar 28 2025
R-4.5-linuxWARNINGMar 28 2025
R-4.4-winWARNINGMar 28 2025
R-4.4-macWARNINGMar 28 2025
R-4.4-linuxWARNINGMar 28 2025
R-4.3-winWARNINGMar 28 2025
R-4.3-macWARNINGMar 28 2025

Exports:LF_ipsimedshiftParam_medshiftpidetest_detmle_medshifttmle3_Spec_medshift

Dependencies:abindassertthatbackportsbase64encBBmiscbitopsbslibcachemcaretcaToolscheckmateclasscliclockcodetoolscolorspacecpp11crayondata.tabledelayeddiagramdigestdplyre1071evaluatefansifarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2globalsgluegowergplotsgtablegtoolshardhathighrhmshtmltoolshtmlwidgetsigraphipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimeModelMetricsmunsellmvtnormnlmennetnumDerivorigamiparallellypillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRdpackrecipesreshape2rlangrmarkdownROCRrpartrstackdequesassscalesshapesl3sparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextmle3tzdbutf8uuidvctrsviridisLitevisNetworkwithrxfunyaml

Causal Mediation Analysis for Stochastic Interventions

Rendered fromintro_medshift.Rmdusingknitr::rmarkdownon Mar 28 2025.

Last update: 2022-01-07
Started: 2019-01-05