{
  "_id": "6a29ed7b7b7a29ca60033b9a",
  "Package": "lmtp",
  "Title": "Non-Parametric Causal Effects of Feasible Interventions Based on\nModified Treatment Policies",
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  "Authors@R": "c(person(given = \"Nicholas\",\nfamily = \"Williams\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"ntwilliams.personal@gmail.com\",\ncomment = c(ORCID = \"0000-0002-1378-4831\")),\nperson(given = \"Iván\",\nfamily = \"Díaz\",\nemail = \"Ivan.Diaz@nyulangone.org\",\nrole = c(\"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-9056-2047\")),\nperson(given = \"Beaudan\",\nfamily = \"Campbell-Brown\",\nrole = c(\"ctb\"),\nemail = \"beaudan.brown@gmail.com\",\ncomment = c(ORCID = \"0009-0006-6967-9295\")),\nperson(given = \"Molly\",\nfamily = \"Davies\",\nrole = c(\"ctb\"),\nemail = \"mollydavies@pinterest.com\"))",
  "Description": "Non-parametric estimators for casual effects based on\nlongitudinal modified treatment policies as described in Diaz,\nWilliams, Hoffman, and Schenck\n<doi:10.1080/01621459.2021.1955691>, traditional point\ntreatment, and traditional longitudinal effects. Continuous,\nbinary, categorical treatments, and multivariate treatments are\nallowed as well are censored outcomes. The treatment mechanism\nis estimated via a density ratio classification procedure\nirrespective of treatment variable type. For both continuous\nand binary outcomes, additive treatment effects can be\ncalculated and relative risks and odds ratios may be calculated\nfor binary outcomes. Supports survival outcomes with competing\nrisks (Diaz, Hoffman, and Hejazi;\n<doi:10.1007/s10985-023-09606-7>).",
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  "BugReports": "https://github.com/nt-williams/lmtp/issues",
  "Repository": "https://nt-williams.r-universe.dev",
  "Date/Publication": "2026-06-10 22:10:47 UTC",
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  "Author": "Nicholas Williams [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-1378-4831>),\nIván Díaz [aut, cph] (ORCID: <https://orcid.org/0000-0001-9056-2047>),\nBeaudan Campbell-Brown [ctb] (ORCID:\n<https://orcid.org/0009-0006-6967-9295>),\nMolly Davies [ctb]",
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