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-4.5)tmle3mediate_0.0.3.zip(r-4.4)tmle3mediate_0.0.3.zip(r-4.3)
tmle3mediate_0.0.3.tgz(r-4.4-any)tmle3mediate_0.0.3.tgz(r-4.3-any)
tmle3mediate_0.0.3.tar.gz(r-4.5-noble)tmle3mediate_0.0.3.tar.gz(r-4.4-noble)
tmle3mediate_0.0.3.tgz(r-4.4-emscripten)tmle3mediate_0.0.3.tgz(r-4.3-emscripten)
tmle3mediate.pdf |tmle3mediate.html✨
tmle3mediate/json (API)
NEWS

# Install 'tmle3mediate' in R:

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

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

On CRAN:

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

2.68 score 3 stars 16 scripts 10 exports 124 dependencies

Last updated 3 years agofrom:70d1151c4a. Checks:ERROR: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	FAIL	Oct 31 2024
R-4.5-win	ERROR	Oct 31 2024
R-4.5-linux	ERROR	Oct 31 2024
R-4.4-win	ERROR	Oct 31 2024
R-4.4-mac	ERROR	Oct 31 2024
R-4.3-win	ERROR	Oct 31 2024
R-4.3-mac	ERROR	Oct 31 2024

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 colorspace cpp11 crayon data.table delayed diagram digest dplyr e1071 evaluate fansi 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 mgcv mime ModelMetrics munsell 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 sass scales shape sl3 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

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)