{ "_id": "6a1022b8acfb0bcc41c8cd3e", "Package": "txshift", "Title": "Efficient Estimation of the Causal Effects of Stochastic\nInterventions", "Version": "0.3.9", "Authors@R": "c(\nperson(\"Nima\", \"Hejazi\", email = \"nh@nimahejazi.org\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-7127-2789\")),\nperson(\"David\", \"Benkeser\", email = \"benkeser@emory.edu\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-1019-8343\")),\nperson(\"Iván\", \"Díaz\", email = \"ild2005@med.cornell.edu\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0001-9056-2047\")),\nperson(\"Jeremy\", \"Coyle\", email = \"jeremy.coyle@gmail.com\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-9874-6649\")),\nperson(\"Mark\", \"van der Laan\", email = \"laan@berkeley.edu\",\nrole = c(\"ctb\", \"ths\"),\ncomment = c(ORCID = \"0000-0003-1432-5511\"))\n)", "Maintainer": "Nima Hejazi ", "Description": "Efficient estimation of the population-level causal\neffects of stochastic interventions on a continuous-valued\nexposure. Both one-step and targeted minimum loss estimators\nare implemented for the counterfactual mean value of an outcome\nof interest under an additive modified treatment policy, a\nstochastic intervention that may depend on the natural value of\nthe exposure. To accommodate settings with outcome-dependent\ntwo-phase sampling, procedures incorporating inverse\nprobability of censoring weighting are provided to facilitate\nthe construction of inefficient and efficient one-step and\ntargeted minimum loss estimators. The causal parameter and its\nestimation were first described by Díaz and van der Laan (2013)\n, while the multiply\nrobust estimation procedure and its application to data from\ntwo-phase sampling designs is detailed in NS Hejazi, MJ van der\nLaan, HE Janes, PB Gilbert, and DC Benkeser (2020)\n. The software package implementation\nis described in NS Hejazi and DC Benkeser (2020)\n. Estimation of nuisance parameters\nmay be enhanced through the Super Learner ensemble model in\n'sl3', available for download from GitHub using\n'remotes::install_github(\"tlverse/sl3\")'.", "License": "MIT + file LICENSE", "URL": "https://github.com/nhejazi/txshift", "BugReports": "https://github.com/nhejazi/txshift/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.2", "RdMacros": "Rdpack", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://nhejazi.r-universe.dev", "Date/Publication": "2024-09-21 20:33:00 UTC", "RemoteUrl": "https://github.com/nhejazi/txshift", "RemoteRef": "HEAD", "RemoteSha": "06ce36d94009e99d21051978b71897139fc06610", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-22 09:28:55 UTC", "User": "root" }, "Author": "Nima Hejazi [aut, cre, cph] (ORCID:\n),\nDavid Benkeser [aut] (ORCID: ),\nIván Díaz [ctb] (ORCID: ),\nJeremy Coyle [ctb] (ORCID: ),\nMark van der Laan [ctb, ths] (ORCID:\n)", "MD5sum": 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