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  "Title": "Estimation of the Proportion of Treatment Effect Explained by\nSurrogate Outcome Information",
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  "Authors@R": "c(person(\"Layla\", \"Parast\", role = c(\"aut\", \"cre\"), email = \"parast@austin.utexas.edu\"), person(\"Xuan\", \"Wang\", role = c(\"aut\"), email = \"xuan.wang@utah.edu\"))",
  "Description": "Provides functions to estimate the proportion of treatment\neffect on a censored primary outcome that is explained by the\ntreatment effect on a censored surrogate outcome/event. All\nmethods are described in detail in Parast, et al (2020)\n\"Assessing the Value of a Censored Surrogate Outcome\"\n<doi:10.1007/s10985-019-09473-1> and Wang et al (2025)\n\"Model-free Approach to Evaluate a Censored Intermediate\nOutcome as a Surrogate for Overall Survival\" (Under Review)\n<doi:10.48550/arXiv.2412.14129>.  A tutorial for this package\ncan be found at <https://www.laylaparast.com/surrogateoutcome>.",
  "License": "GPL",
  "Repository": "https://laylaparast.r-universe.dev",
  "Date/Publication": "2026-01-07 11:17:08 UTC",
  "RemoteUrl": "https://github.com/laylaparast/surrogateoutcome",
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      "title": "Calculates the incremental value of the surrogate outcome information",
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      "title": "Calculates the proportion of the treatment effect (the difference in restricted mean survival time at time t) explained by primary outcome information observed up to the landmark time",
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