simcausal: Simulating Longitudinal Data with Causal Inference Applications
Version 0.5.4

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.

Package details

AuthorOleg Sofrygin [aut, cre], Mark J. van der Laan [aut], Romain Neugebauer [aut]
Date of publication2017-10-08 21:59:05 UTC
MaintainerOleg Sofrygin <[email protected]>
Package repositoryView on CRAN
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simcausal documentation built on Oct. 9, 2017, 1:03 a.m.