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gcomputation  

Causal Inference by using G-Computation
View on CRAN: Click here


Download and install gcomputation package within the R console
Install from CRAN:
install.packages("gcomputation")

Install from Github:
library("remotes")
install_github("cran/gcomputation")

Install by package version:
library("remotes")
install_version("gcomputation", "0.34")



Attach the package and use:
library("gcomputation")
Maintained by
Yohann Foucher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-11
Latest Update: 2026-05-11
Description:
Several functions and S3 methods for G-computation and emulation of clinical trials. It allows for flexible estimation of the outcome model, especiallypenalized regressions (Lasso, Ridge, or Elasticnet) for binary, continuous, counting, or right-censored time-to-event outcomes. Average treatment effect among the entire population (ATE) or among the treated population (ATT) can be estimated. The method for time-to-events is described by Chatton et al. (2020) <doi:10.1038/s41598-020-65917-x>.For a binary outcome, details are available in the paper proposed by Chatton et al. (2022) <doi:10.1177/09622802211047345>.
How to cite:
Yohann Foucher (2026). gcomputation: Causal Inference by using G-Computation. R package version 0.34, https://cran.r-project.org/web/packages/gcomputation. Accessed 24 Oct. 2026.
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