{
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  "Package": "dbw",
  "Title": "Doubly Robust Distribution Balancing Weighting Estimation",
  "Version": "1.1.4",
  "Authors@R": "person(\"Hiroto\", \"Katsumata\",\nemail = \"hrt.katsumata@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-5901-8844\"))",
  "Description": "Implements the doubly robust distribution balancing\nweighting proposed by Katsumata (2024)\n<doi:10.1017/psrm.2024.23>, which improves the augmented\ninverse probability weighting (AIPW) by estimating propensity\nscores with estimating equations suitable for the pre-specified\nparameter of interest (e.g., the average treatment effects or\nthe average treatment effects on the treated) and estimating\noutcome models with the estimated inverse probability weights.\nIt also implements the covariate balancing propensity score\nproposed by Imai and Ratkovic (2014) <doi:10.1111/rssb.12027>\nand the entropy balancing weighting proposed by Hainmueller\n(2012) <doi:10.1093/pan/mpr025>, both of which use covariate\nbalancing conditions in propensity score estimation. The point\nestimate of the parameter of interest and its uncertainty as\nwell as coefficients for propensity score estimation and\noutcome regression are produced using the M-estimation. The\nsame functions can be used to estimate average outcomes in\nmissing outcome cases.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.2.3",
  "URL": "https://github.com/hirotokatsumata/dbw",
  "BugReports": "https://github.com/hirotokatsumata/dbw/issues",
  "Repository": "https://hirotokatsumata.r-universe.dev",
  "Date/Publication": "2024-08-28 12:06:40 UTC",
  "RemoteUrl": "https://github.com/hirotokatsumata/dbw",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-06 08:38:26 UTC",
    "User": "root"
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  "Author": "Hiroto Katsumata [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0001-5901-8844>)",
  "Maintainer": "Hiroto Katsumata <hrt.katsumata@gmail.com>",
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      "title": "Doubly robust distribution balancing weighting (DBW) estimation",
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