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]

medshift_0.1.4.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
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

3.74 score 10 stars 11 scripts 7 exports 122 dependencies

Last updated from:0ae0572fc5. Checks:7 WARNING, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING279
source / vignettesOK292
linux-release-x86_64WARNING292
macos-release-arm64WARNING203
macos-oldrel-arm64WARNING177
windows-develWARNING238
windows-releaseWARNING241
windows-oldrelWARNING219
wasm-releaseOK174

Exports:LF_ipsimedshiftParam_medshiftpidetest_detmle_medshifttmle3_Spec_medshift

Dependencies:abindassertthatbackportsbase64encBBmiscbitopsbslibcachemcaretcaToolscheckmateclasscliclockcodetoolscpp11crayondata.tabledelayeddiagramdigestdplyre1071evaluatefarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2globalsgluegowergplotsgtablegtoolshardhathighrhmshtmltoolshtmlwidgetsigraphipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmemoisemimeModelMetricsmvtnormnlmennetnumDerivorigamiparallellypillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrR.methodsS3R.ooR.utilsR6rappdirsrbibutilsRColorBrewerRcppRdpackrecipesreshape2rlangrmarkdownROCRrpartrstackdequeS7sassscalesshapesl3sparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetinytextmle3tzdbutf8uuidvctrsviridisLitevisNetworkwithrxfunyaml

Causal Mediation Analysis for Stochastic Interventions

Nima Hejazi and Iván Díaz

Rendered fromintro_medshift.Rmdusingknitr::rmarkdownon May 16 2026.

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