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.
Version: 0.5.7 Depends: R (≥ 3.2.0) Imports: data.table, igraph, stringr, R6, assertthat, Matrix, methods Suggests: copula, RUnit, ltmle, knitr, ggplot2, Hmisc, mvtnorm, bindata Published: 2024-10-19 DOI: 10.32614/CRAN.package.simcausal Author: Oleg Sofrygin [aut], Mark J. van der Laan [aut], Romain Neugebauer [aut], Fred Gruber [ctb, cre] Maintainer: Fred Gruber <fgruber at gmail.com> BugReports: https://github.com/osofr/simcausal/issues License: GPL-2 URL: https://github.com/osofr/simcausal NeedsCompilation: no Citation: simcausal citation info Materials: README NEWS CRAN checks: simcausal results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=simcausal to link to this page.
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