This package is considered a duplicate. The official version of this package is found at:https://tlverse.r-universe.dev/tmle3mediate

Package: tmle3mediate 0.0.3

Nima Hejazi

tmle3mediate: Targeted Learning for Causal Mediation Analysis

Targeted maximum likelihood (TML) estimation of population-level causal effects in mediation analysis. The causal effects are defined by joint static or stochastic interventions applied to the exposure and the mediator. Targeted doubly robust estimators are provided for the classical natural direct and indirect effects, as well as the more recently developed population intervention direct and indirect effects.

Authors:Nima Hejazi [aut, cre, cph], James Duncan [aut], David McCoy [aut], Mark van der Laan [ctb, ths]

tmle3mediate_0.0.3.tar.gz
tmle3mediate_0.0.3.zip(r-4.7)tmle3mediate_0.0.3.zip(r-4.6)tmle3mediate_0.0.3.zip(r-4.5)
tmle3mediate_0.0.3.tgz(r-4.6-any)tmle3mediate_0.0.3.tgz(r-4.5-any)
tmle3mediate_0.0.3.tar.gz(r-4.7-any)tmle3mediate_0.0.3.tar.gz(r-4.6-any)
tmle3mediate_0.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tmle3mediate/json (API)
NEWS

# Install 'tmle3mediate' in R:

install.packages('tmle3mediate', repos = c('https://ictml-project.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tlverse/tmle3mediate/issues

Pkgdown/docs site:https://tlverse.org

On CRAN:

causal-inference causal-mediation-analysis machine-learning mediation-analysis stochastic-interventions targeted-learning treatment-effects

3.00 score 5 stars 20 scripts 10 exports 122 dependencies

Last updated from:70d1151c4a. Checks:8 ERROR, 1 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	ERROR	240
source / vignettes	ERROR	317
linux-release-x86_64	ERROR	262
macos-release-arm64	ERROR	205
macos-oldrel-arm64	ERROR	224
windows-devel	ERROR	225
windows-release	ERROR	209
windows-oldrel	ERROR	204
wasm-release	OK	158

Exports:LF_ipsi Param_medshift Param_NDE Param_NIE tmle_medshift tmle_NDE tmle_NIE tmle3_Spec_medshift tmle3_Spec_NDE tmle3_Spec_NIE

Dependencies:abind assertthat backports base64enc BBmisc bitops bslib cachem caret caTools checkmate class cli clock codetools cpp11 crayon data.table delayed diagram digest dplyr e1071 evaluate farver fastmap fontawesome foreach fs future future.apply generics ggplot2 globals glue gower gplots gtable gtools hardhat highr hms htmltools htmlwidgets igraph ipred isoband iterators jquerylib jsonlite KernSmooth knitr labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix memoise mime ModelMetrics mvtnorm nlme nnet numDeriv origami parallelly pillar pkgconfig plyr prettyunits pROC prodlim progress progressr proxy purrr R.methodsS3 R.oo R.utils R6 rappdirs rbibutils RColorBrewer Rcpp Rdpack recipes reshape2 rlang rmarkdown ROCR rpart rstackdeque S7 sass scales shape sl3 sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tinytex tmle3 tzdb utf8 uuid vctrs viridisLite visNetwork withr xfun yaml

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
Likelihood Factor for Incremental Propensity Score Interventions	LF_ipsi
Parameter for the Population Intervention (In)direct Effects	Param_medshift
Parameter for the natural direct effect	Param_NDE
Parameter for the natural indirect effect	Param_NIE
TML Estimator for the Population Intervention (In)direct Effects	tmle_medshift
TML Estimator for the Natural Direct Effect	tmle_NDE
TML Estimator for the Natural Indirect Effect	tmle_NIE
TML Estimator for the Population Intervention (In)direct Effects	tmle3_Spec_medshift
TML Estimator for the Natural Direct Effect	tmle3_Spec_NDE
TML Estimator for the Natural Indirect Effect	tmle3_Spec_NIE

Package: tmle3mediate 0.0.3

tmle3mediate: Targeted Learning for Causal Mediation Analysis

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