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  "Package": "BiostatsUHNplus",
  "Title": "Nested Data Summary, Adverse Events and REDCap",
  "Version": "1.0.5",
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  "Description": "Tools and code snippets for summarizing nested data,\nadverse events and REDCap study information.",
  "License": "MIT + file LICENSE",
  "Config/testthat/edition": "3",
  "Encoding": "UTF-8",
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  "Collate": "'data.R' 'globals.R' 'as_numeric_parse.R' 'covsum_nested.R'\n'dsmb_ccru.R' 'nice_mcmcglmm.R' 'nice_mcmcglmm_icc.R'\n'ae_timeline_plot.R' 'caterpillar_plot.R' 'redcap_data_out.R'\n'rm_ae_all_g3p.R' 'dsmb_ddp.R'",
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  "Author": "Lisa Avery [aut] (ORCID:\n<https://orcid.org/0000-0002-8431-5143>), Zeynep Baskurt [aut],\nOsvaldo Espin-Garcia [aut], Katrina Hueniken [aut], Katherine\nLajkosz [aut] (ORCID: <https://orcid.org/0000-0003-3760-5401>),\nXuan Li [aut], Tyler Pittman [cre, aut] (ORCID:\n<https://orcid.org/0000-0002-5013-6980>), Anna Santiago [aut]\n(ORCID: <https://orcid.org/0000-0002-0932-2386>), Jessica Weiss\n[aut], Wei Xu [aut]",
  "Maintainer": "Tyler Pittman <tyler.pittman@uhn.ca>",
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  "Repository": "https://tylerpittman.r-universe.dev",
  "Date/Publication": "2026-09-07 20:39:32 UTC",
  "RemoteUrl": "https://github.com/cran/BiostatsUHNplus",
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      "title": "Simulated adverse events for patients receiving two study agents.",
      "object": "ae",
      "class": [
        "data.frame"
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      "fields": [
        "Subject",
        "ae_detail",
        "ae_category",
        "CTCAE5_LLT_NM",
        "AE_VERBATIM_TRM_TXT",
        "AE_SEV_GD",
        "AE_ONSET_DT_INT",
        "CTC_AE_ATTR_SCALE",
        "CTC_AE_ATTR_SCALE_1"
      ],
      "rows": 349,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Simulated demography for patients.",
      "object": "demography",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Subject",
        "GENDER_CODE"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "drug1_admin",
      "title": "Simulated study agent 1 for patients.",
      "object": "drug1_admin",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "TX1_DATE_INT"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "drug2_admin",
      "title": "Simulated study agent 2 for patients.",
      "object": "drug2_admin",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Subject",
        "TX2_DATE_INT"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "enrollment",
      "title": "Enrollment data Simulated enrollment for patients.",
      "object": "enrollment",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Subject",
        "COHORT",
        "ENROL_DATE_INT"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "ineligibility",
      "title": "Simulated ineligibility for patients.",
      "object": "ineligibility",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Subject",
        "INELIGIBILITY_STATUS"
      ],
      "rows": 11,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "ae",
      "title": "Simulated adverse events for patients receiving two study agents.",
      "topics": [
        "ae"
      ]
    },
    {
      "page": "ae_timeline_plot",
      "title": "Outputs related adverse event timeline plots including just system organ class (AE category), or system organ class and lowest level term (AE detail). This function can fit up to 5 different attributions. Modify width, height and scale parameters in ggsave() to customize fit for large plot.",
      "topics": [
        "ae_timeline_plot"
      ]
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      "topics": [
        "as_numeric_parse"
      ]
    },
    {
      "page": "caterpillar_plot",
      "title": "Caterpillar plot. Useful for plotting random effects from hierarchical models, such as MCMCglmm::MCMCglmm() object, that have binary outcome.",
      "topics": [
        "caterpillar_plot"
      ]
    },
    {
      "page": "covsum_nested",
      "title": "Nested version of reportRmd covsum()",
      "topics": [
        "covsum_nested"
      ]
    },
    {
      "page": "demography",
      "title": "Simulated demography for patients.",
      "topics": [
        "demography"
      ]
    },
    {
      "page": "drug1_admin",
      "title": "Simulated study agent 1 for patients.",
      "topics": [
        "drug1_admin"
      ]
    },
    {
      "page": "drug2_admin",
      "title": "Simulated study agent 2 for patients.",
      "topics": [
        "drug2_admin"
      ]
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      "topics": [
        "dsmb_ccru"
      ]
    },
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      "topics": [
        "dsmb_ddp"
      ]
    },
    {
      "page": "enrollment",
      "title": "Enrollment data Simulated enrollment for patients.",
      "topics": [
        "enrollment"
      ]
    },
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      ]
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      ]
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      "title": "Outputs a nested version of reportRmd::rm_covsum()",
      "topics": [
        "rm_covsum_nested"
      ]
    }
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