{ "_id": "6ac9ee5ffe5cc25786e82ebe", "Package": "CausalState", "Type": "Package", "Title": "Causal Inference in a Longitudinal Transitioning State\nEnvironment", "Version": "0.10.2", "Authors@R": "person(given = \"Sebastiaan\",\nfamily = \"Blank\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"sebastiaan.blank@mail.com\",\ncomment = c(ORCID = \"0000-0001-9115-2138\"))", "Description": "Implements Sequential Doubly Robust (SDR) and\ninfinite-dimensional Targeted Maximum Likelihood (iTMLE)\nestimators for longitudinal modified treatment policies in\nsettings with transitioning states, such as ICU, ward, or\nemergency department care episodes. Treatment is permitted in\nactive states and becomes structurally inapplicable after a\nstate transition (e.g. discharge or death). Supports asymmetric\ng- and Q-model regularisation, k-fold cross-fitting, and\npluggable SuperLearner ensembles. 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