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  "Package": "psrwe",
  "Title": "PS-Integrated Methods for Incorporating RWE in Clinical Studies",
  "Version": "3.2",
  "Authors@R": "c(\nperson(given = \"Chenguang\", family = \"Wang\",\nemail = \"chenguang.wang.0517@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Trustees of Columbia University\",\nrole = \"cph\",\ncomment = \"tools/make_cpp.R, R/stanmodels.R\"),\nperson(given = \"Wei-Chen\", family = \"Chen\",\nrole = c(\"aut\")))",
  "Description": "High-quality real-world data can be transformed into\nscientific real-world evidence (RWE) for regulatory and\nhealthcare decision-making using proven analytical methods and\ntechniques. For example, propensity score (PS) methodology can\nbe applied to pre-select a subset of real-world data containing\npatients that are similar to those in the current clinical\nstudy in terms of covariates, and to stratify the selected\npatients together with those in the current study into more\nhomogeneous strata. Then, methods such as the power prior\napproach or composite likelihood approach can be applied in\neach stratum to draw inference for the parameters of interest.\nThis package provides functions that implement the\nPS-integrated RWE analysis methods proposed in Wang et al.\n(2019) <doi:10.1080/10543406.2019.1657133>, Wang et al. (2020)\n<doi:10.1080/10543406.2019.1684309> and Chen et al. (2020)\n<doi:10.1080/10543406.2020.1730877>.",
  "License": "GPL (>= 3)",
  "URL": "https://github.com/olssol/psrwe",
  "BugReports": "https://github.com/olssol/psrwe/issues",
  "Encoding": "UTF-8",
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  "Repository": "https://olssol.r-universe.dev",
  "Date/Publication": "2024-07-16 16:49:11 UTC",
  "RemoteUrl": "https://github.com/olssol/psrwe",
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  "Packaged": {
    "Date": "2026-05-16 06:57:51 UTC",
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  "Author": "Chenguang Wang [aut, cre],\nTrustees of Columbia University [cph] (tools/make_cpp.R,\nR/stanmodels.R),\nWei-Chen Chen [aut]",
  "Maintainer": "Chenguang Wang <chenguang.wang.0517@gmail.com>",
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    "extra/citation.json",
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    },
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    "psrwe_borrow",
    "psrwe_ci",
    "psrwe_compl",
    "psrwe_compl_watt",
    "psrwe_est",
    "psrwe_infer",
    "psrwe_match",
    "psrwe_outana",
    "psrwe_powerp",
    "psrwe_powerp_watt",
    "psrwe_survkm",
    "psrwe_survlrk",
    "psrwe_survrmst",
    "rwe_cl",
    "rwe_cl_watt",
    "rwe_cut",
    "rwe_km",
    "rwe_lrk",
    "rwe_rmst",
    "rwe_stan"
  ],
  "_datasets": [
    {
      "name": "ex_dta",
      "title": "Example dataset",
      "object": "ex_dta",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "Y_Bin",
        "Y_Con",
        "Y_Surv",
        "Status",
        "V1",
        "V2",
        "V3",
        "V4",
        "V5",
        "V6",
        "V7"
      ],
      "rows": 1231,
      "table": true,
      "tojson": true
    },
    {
      "name": "ex_dta_rct",
      "title": "Example dataset",
      "object": "ex_dta_rct",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Group",
        "Arm",
        "Y_Con",
        "V1",
        "V2",
        "V3",
        "V4",
        "V5",
        "V6",
        "V7",
        "Y_Surv",
        "Status"
      ],
      "rows": 1231,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "psrwe-package",
      "title": "PS-Integrated Methods for Incorporating RWE in Clinical Studies",
      "topics": [
        "psrwe-package",
        "psrwe"
      ]
    },
    {
      "page": "ex_dta",
      "title": "Example dataset",
      "topics": [
        "ex_dta"
      ]
    },
    {
      "page": "ex_dta_rct",
      "title": "Example dataset",
      "topics": [
        "ex_dta_rct"
      ]
    },
    {
      "page": "get_distance",
      "title": "Distance between two distributions",
      "topics": [
        "get_distance"
      ]
    },
    {
      "page": "plot.PSRWE_DTA",
      "title": "Plot PS distributions",
      "topics": [
        "plot.PSRWE_DTA"
      ]
    },
    {
      "page": "plot.PSRWE_DTA_MAT",
      "title": "Plot PS distributions",
      "topics": [
        "plot.PSRWE_DTA_MAT"
      ]
    },
    {
      "page": "plot.PSRWE_RST",
      "title": "Plot estimation results for power prior approach",
      "topics": [
        "plot.PSRWE_RST"
      ]
    },
    {
      "page": "print.PSRWE_BOR",
      "title": "Print borrow information",
      "topics": [
        "print.PSRWE_BOR"
      ]
    },
    {
      "page": "print.PSRWE_DTA",
      "title": "Print PS estimation results",
      "topics": [
        "print.PSRWE_DTA"
      ]
    },
    {
      "page": "print.PSRWE_DTA_MAT",
      "title": "Print PS estimation results",
      "topics": [
        "print.PSRWE_DTA_MAT"
      ]
    },
    {
      "page": "print.PSRWE_RST",
      "title": "Print estimation results",
      "topics": [
        "print.PSRWE_RST"
      ]
    },
    {
      "page": "print.PSRWE_RST_OUTANA",
      "title": "Print outcome analysis results",
      "topics": [
        "print.PSRWE_RST_OUTANA"
      ]
    },
    {
      "page": "psrwe_borrow",
      "title": "Get number of subjects borrowed from each statum",
      "topics": [
        "psrwe_borrow"
      ]
    },
    {
      "page": "psrwe_ci",
      "title": "Confidence/Credible Interval for PS-Integrated Estimation",
      "topics": [
        "psrwe_ci"
      ]
    },
    {
      "page": "psrwe_compl",
      "title": "PS-Integrated Composite Likelihood Estimation",
      "topics": [
        "psrwe_compl"
      ]
    },
    {
      "page": "psrwe_compl_watt",
      "title": "PS-Integrated Composite Likelihood Estimation (WATT)",
      "topics": [
        "psrwe_compl_watt"
      ]
    },
    {
      "page": "psrwe_est",
      "title": "Estimate propensity scores",
      "topics": [
        "psrwe_est"
      ]
    },
    {
      "page": "psrwe_infer",
      "title": "Inference for the PS-Integrated Estimation",
      "topics": [
        "psrwe_infer"
      ]
    },
    {
      "page": "psrwe_match",
      "title": "PS matching",
      "topics": [
        "psrwe_match"
      ]
    },
    {
      "page": "psrwe_outana",
      "title": "Outcome Analysis for PS-Integrated Estimation",
      "topics": [
        "psrwe_outana"
      ]
    },
    {
      "page": "psrwe_powerp",
      "title": "Get posterior samples based on PS-power prior approach",
      "topics": [
        "psrwe_powerp"
      ]
    },
    {
      "page": "psrwe_powerp_watt",
      "title": "Get posterior samples based on PS-power prior approach (WATT)",
      "topics": [
        "psrwe_powerp_watt"
      ]
    },
    {
      "page": "psrwe_survkm",
      "title": "PS-Integrated Kaplan-Meier Estimation",
      "topics": [
        "psrwe_survkm"
      ]
    },
    {
      "page": "psrwe_survlrk",
      "title": "PS-Integrated Log-Rank Test For Comparing Time-to-event Outcomes",
      "topics": [
        "psrwe_survlrk"
      ]
    },
    {
      "page": "psrwe_survrmst",
      "title": "PS-Integrated Restricted Mean Survival Time (RMST) Test For Comparing Time-to-event Outcomes",
      "topics": [
        "psrwe_survrmst"
      ]
    },
    {
      "page": "rwe_cl",
      "title": "Composite Likelihood Estimation",
      "topics": [
        "rwe_cl"
      ]
    },
    {
      "page": "rwe_cl_watt",
      "title": "Composite Likelihood Estimation (WATT)",
      "topics": [
        "rwe_cl_watt"
      ]
    },
    {
      "page": "rwe_cut",
      "title": "Create strata",
      "topics": [
        "rwe_cut"
      ]
    },
    {
      "page": "rwe_km",
      "title": "Kaplan-Meier Estimation",
      "topics": [
        "rwe_km"
      ]
    },
    {
      "page": "rwe_lrk",
      "title": "Log-rank Estimation",
      "topics": [
        "rwe_lrk"
      ]
    },
    {
      "page": "rwe_rmst",
      "title": "RMST Estimation",
      "topics": [
        "rwe_rmst"
      ]
    },
    {
      "page": "rwe_stan",
      "title": "Call STAN models",
      "topics": [
        "rwe_stan"
      ]
    },
    {
      "page": "summary.PSRWE_DTA",
      "title": "Summarize PS estimation and stratification results",
      "topics": [
        "summary.PSRWE_DTA"
      ]
    },
    {
      "page": "summary.PSRWE_DTA_MAT",
      "title": "Summarize PS estimation and matching results",
      "topics": [
        "summary.PSRWE_DTA_MAT"
      ]
    },
    {
      "page": "summary.PSRWE_RST",
      "title": "Summarize overall estimation results",
      "topics": [
        "summary.PSRWE_RST"
      ]
    },
    {
      "page": "summary.PSRWE_RST_OUTANA",
      "title": "Summary outcome analysis results",
      "topics": [
        "summary.PSRWE_RST_OUTANA"
      ]
    }
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      "title": "psrwe: Propensity Score-Integrated Methods for Incorporating Real-World Evidence in Clinical Studies",
      "author": "Chenguang Wang",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
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