{ "_id": "6a1016a8acfb0bcc41c849bf", "Package": "simcausal", "Type": "Package", "Version": "0.5.5", "Title": "Simulating Longitudinal Data with Causal Inference Applications", "Authors@R": "c(\nperson(\"Oleg\", \"Sofrygin\", role=c(\"aut\", \"cre\"), email=\"oleg.sofrygin@gmail.com\"),\nperson(c(\"Mark\", \"J.\"), \"van der Laan\", role=\"aut\", email=\"laan@berkeley.edu\"),\nperson(\"Romain\", \"Neugebauer\", role=\"aut\", email=\"Romain.S.Neugebauer@kp.org\"))", "Description": "A flexible tool for simulating complex longitudinal data\nusing structural equations, with emphasis on problems in causal\ninference. Specify interventions and simulate from intervened\ndata generating distributions. Define and evaluate\ntreatment-specific means, the average treatment effects and\ncoefficients from working marginal structural models. User\ninterface designed to facilitate the conduct of transparent and\nreproducible simulation studies, and allows concise expression\nof complex functional dependencies for a large number of\ntime-varying nodes. 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