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  "Title": "Tidy Presentation of Clinical Reporting",
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  "Description": "Streamlined statistical reporting in 'Rmarkdown'\nenvironments. Facilitates the automated reporting of\ndescriptive statistics, multiple univariate models,\nmultivariable models and tables combining these outputs.\nPlotting functions include customisable survival curves, forest\nplots from logistic and ordinal regression and bivariate\ncomparison plots.",
  "License": "MIT + file LICENSE",
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  "Author": "Lisa Avery [cre, aut] (ORCID: <https://orcid.org/0000-0002-8431-5143>),\nRyan Del Bel [aut],\nOsvaldo Espin-Garcia [aut],\nKatherine Lajkosz [aut] (ORCID:\n<https://orcid.org/0000-0003-3760-5401>),\nClarina Ong [aut],\nTyler Pittman [aut] (ORCID: <https://orcid.org/0000-0002-5013-6980>),\nAnna Santiago [aut] (ORCID: <https://orcid.org/0000-0002-0932-2386>),\nYanning Wang [ctr],\nJessica Weiss [aut],\nWei Xu [aut]",
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    "rm_survtime",
    "rm_uv_mv",
    "rm_uvsum",
    "scrolling_table",
    "set_labels",
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      "title": "Tumour size change over time Longitudinal changes in tumour size since baseline for patients by changes in ctDNA status (clearance, decrease or increase) since baseline.",
      "object": "ctDNA",
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      "class": [
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        "tbl",
        "data.frame"
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        "cohort",
        "ctdna_status",
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        "size_change"
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      "table": true,
      "tojson": true
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      "object": "pembrolizumab",
      "file": "pembrolizumab.rda",
      "class": [
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        "tbl",
        "data.frame"
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        "age",
        "sex",
        "cohort",
        "l_size",
        "pdl1",
        "tmb",
        "baseline_ctdna",
        "change_ctdna_group",
        "orr",
        "cbr",
        "os_status",
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        "pfs_status",
        "pfs_time"
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      "rows": 94,
      "table": true,
      "tojson": true
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      "title": "Add censor marks to KM plot",
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    },
    {
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      "topics": [
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    },
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    },
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    },
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      "topics": [
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    },
    {
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      "topics": [
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    },
    {
      "page": "calculate_and_add_median_times",
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      "topics": [
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    },
    {
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      "topics": [
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    },
    {
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      "topics": [
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    },
    {
      "page": "calculate_cif_timepoints",
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      "topics": [
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      "page": "covsum",
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      "topics": [
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    {
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      "topics": [
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    },
    {
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      "topics": [
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    },
    {
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      "topics": [
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    },
    {
      "page": "create_km_dataframe",
      "title": "Create plotting dataframe for KM curves",
      "topics": [
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    },
    {
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      "title": "Create risk table for survival plot",
      "topics": [
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    },
    {
      "page": "crrRx",
      "title": "fit crr model",
      "topics": [
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    },
    {
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      "topics": [
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    },
    {
      "page": "excelCol",
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      "topics": [
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      ]
    },
    {
      "page": "excelColLetters",
      "title": "Retrieve spreadsheet column letter-names from columns indices",
      "topics": [
        "excelColLetters"
      ]
    },
    {
      "page": "extract_grays_test",
      "title": "Extract Gray's test results from CIF fit",
      "topics": [
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    },
    {
      "page": "extract_labels",
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      "topics": [
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    },
    {
      "page": "extract_package_details",
      "title": "Extract Function and Package Information from Current Document",
      "topics": [
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    },
    {
      "page": "fit_cif_model",
      "title": "Fit Competing Risks Model",
      "topics": [
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    },
    {
      "page": "fit_km_model",
      "title": "Fit Kaplan-Meier survival curves",
      "topics": [
        "fit_km_model"
      ]
    },
    {
      "page": "forestplot2",
      "title": "Create a forest plot using ggplot2 (DEPRECATED)",
      "topics": [
        "forestplot2"
      ]
    },
    {
      "page": "forestplotMV",
      "title": "Create a multivariable forest plot using ggplot2",
      "topics": [
        "forestplotMV"
      ]
    },
    {
      "page": "forestplotUV",
      "title": "Create a univariable forest plot using ggplot2",
      "topics": [
        "forestplotUV"
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    },
    {
      "page": "forestplotUVMV",
      "title": "Combine univariable and multivariable forest plot (DEPRECATED)",
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    },
    {
      "page": "geoR_boxcoxfit",
      "title": "Parameter Estimation for the Box-Cox Transformation",
      "topics": [
        "geoR_boxcoxfit"
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    },
    {
      "page": "ggkmcif_paste",
      "title": "combine components of a call to ggkmci",
      "topics": [
        "ggkmcif_paste"
      ]
    },
    {
      "page": "ggkmcif2",
      "title": "Plot KM and CIF curves with ggplot",
      "topics": [
        "ggkmcif2"
      ]
    },
    {
      "page": "ggkmcif2Parameters",
      "title": "Additional parameters passed to ggkmcif2",
      "topics": [
        "ggkmcif2Parameters"
      ]
    },
    {
      "page": "hbld",
      "title": "Bold strings for HTML output",
      "topics": [
        "hbld"
      ]
    },
    {
      "page": "lpvalue2",
      "title": "Format p-values for plot annotations",
      "topics": [
        "lpvalue2"
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    },
    {
      "page": "mvsum",
      "title": "Get multivariate summary dataframe",
      "topics": [
        "mvsum"
      ]
    },
    {
      "page": "nestTable",
      "title": "Combine two table columns into a single column with levels of one nested within levels of the other.",
      "topics": [
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    },
    {
      "page": "outTable",
      "title": "Print tables to PDF/Latex HTML or Word",
      "topics": [
        "outTable"
      ]
    },
    {
      "page": "pembrolizumab",
      "title": "Survival data Survival status and ctDNA levels for patients receiving pembrolizumab",
      "topics": [
        "pembrolizumab"
      ]
    },
    {
      "page": "plotuv",
      "title": "Plot multiple bivariate relationships in a single plot",
      "topics": [
        "plotuv"
      ]
    },
    {
      "page": "predsum",
      "title": "Summarise Performance of a Prediction Model",
      "topics": [
        "predsum"
      ]
    },
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