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simcausal  

Simulating Longitudinal Data with Causal Inference Applications
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("simcausal", "0.5.7")



Attach the package and use:
library("simcausal")
Maintained by
Fred Gruber
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-05-16
Latest Update: 2024-10-19
Description:
A flexible tool for simulating complex longitudinal data using structural equations, with emphasis on problems in causal inference. Specify interventions and simulate from intervened data generating distributions. Define and evaluate treatment-specific means, the average treatment effects and coefficients from working marginal structural models. User interface designed to facilitate the conduct of transparent and reproducible simulation studies, and allows concise expression of complex functional dependencies for a large number of time-varying nodes. See the package vignette for more information, documentation and examples.
How to cite:
Fred Gruber (2015). simcausal: Simulating Longitudinal Data with Causal Inference Applications. R package version 0.5.7, https://cran.r-project.org/web/packages/simcausal. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:04), 0.1 (2015-05-16 09:52), 0.2.0 (2015-06-13 00:41), 0.3.0 (2015-08-24 15:55), 0.4.0 (2015-09-22 00:52), 0.5.0 (2016-02-20 08:55), 0.5.1 (2016-05-25 06:29), 0.5.3 (2016-12-20 02:08), 0.5.4 (2017-10-08 23:59), 0.5.5 (2019-01-08 00:40), 0.5.6 (2022-10-28 13:52)
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Complete documentation for simcausal
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