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.

Maintainer: Oleg Sofrygin <oleg.sofrygin at gmail.com>

Author(s): Oleg Sofrygin*, Mark J. van der Laan*, Romain Neugebauer*

Install package and any missing dependencies by running this line in your R console:

install.packages("simcausal")

Depends R (>= 3.2.0)
Imports data.table, igraph, stringr, R6, assertthat, Matrix, methods
Suggests tmlenet, RUnit, ltmle, knitr, ggplot2, Hmisc, copula, mvtnorm, bindata
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Package simcausal
Materials
URL https://github.com/osofr/simcausal
Task Views
Version 0.5.3
Published 2016-12-20
License GPL-2
BugReports https://github.com/osofr/simcausal/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks simcausal check results
Package source simcausal_0.5.3.tar.gz