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  "Package": "pseudoCure",
  "Title": "A Pseudo-Observations Approach for Analyzing Survival Data with\na Cure Fraction",
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  "Authors@R": "c(person(given = \"Sy Han (Steven)\", family = \"Chiou\",\nemail = \"schiou@smu.edu\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Chien-Lin\", family = \" Su\",\nemail = \"marksu740824@gmail.com\", role = \"aut\"),\nperson(given = \"Feng-Chang\", family = \" Lin\",\nemail = \"flin@bios.unc.edu\", role = \"aut\"))",
  "Date": "2025-02-05",
  "Description": "A collection of easy-to-use tools for regression analysis\nof survival data with a cure fraction proposed in Su et al.\n(2022) <doi:10.1177/09622802221108579>. The modeling framework\nis based on the Cox proportional hazards mixture cure model and\nthe bounded cumulative hazard (promotion time cure) model. The\npseudo-observations approach is utilized to assess covariate\neffects and embedded in the variable selection procedure.",
  "License": "GPL (>= 2)",
  "RoxygenNote": "7.3.2",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-01 11:37:16 UTC",
    "User": "root"
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  "Encoding": "UTF-8",
  "Author": "Sy Han (Steven) Chiou [aut, cre], Chien-Lin Su [aut],\nFeng-Chang Lin [aut]",
  "Maintainer": "Sy Han (Steven) Chiou <schiou@smu.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-02-06 13:10:02 UTC",
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