{
  "_id": "6a116875acfb0bcc41cf27a1",
  "Package": "JointAI",
  "Version": "1.1.0",
  "Title": "Joint Analysis and Imputation of Incomplete Data",
  "Authors@R": "c(person(\"Nicole S.\", \"Erler\", email = \"n.s.erler@umcutrecht.nl\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-9370-6832\")))",
  "Description": "Joint analysis and imputation of incomplete data in the\nBayesian framework, using (generalized) linear (mixed) models\nand extensions there of, survival models, or joint models for\nlongitudinal and survival data, as described in Erler,\nRizopoulos and Lesaffre (2021) <doi:10.18637/jss.v100.i20>.\nIncomplete covariates, if present, are automatically imputed.\nThe package performs some preprocessing of the data and creates\na 'JAGS' model, which will then automatically be passed to\n'JAGS' <https://mcmc-jags.sourceforge.io/> with the help of the\npackage 'rjags'.",
  "URL": "https://nerler.github.io/JointAI/",
  "License": "GPL (>= 2)",
  "BugReports": "https://github.com/nerler/JointAI/issues/",
  "LazyData": "TRUE",
  "RoxygenNote": "7.3.3",
  "Roxygen": "list(old_usage = TRUE, markdown = TRUE)",
  "SystemRequirements": "JAGS (https://mcmc-jags.sourceforge.io/)",
  "VignetteBuilder": "knitr",
  "Encoding": "UTF-8",
  "RdMacros": "mathjaxr",
  "Config/testthat/edition": "3",
  "Language": "en-GB",
  "Config/pak/sysreqs": "cmake libfftw3-dev make jags libuv1-dev",
  "Repository": "https://nerler.r-universe.dev",
  "Date/Publication": "2026-02-22 17:10:10 UTC",
  "RemoteUrl": "https://github.com/nerler/jointai",
  "RemoteRef": "HEAD",
  "RemoteSha": "ab46e5a5cd0ac998140f92af67619845a3d10509",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-23 08:38:03 UTC",
    "User": "root"
  },
  "Author": "Nicole S. Erler [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-9370-6832>)",
  "Maintainer": "Nicole S. Erler <n.s.erler@umcutrecht.nl>",
  "MD5sum": "6eb566028719dd9cb7249b7d8423d565",
  "_user": "nerler",
  "_type": "src",
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  "_created": "2026-05-23T08:38:03.000Z",
  "_published": "2026-05-23T08:42:29.586Z",
  "_distro": "noble",
  "_jobs": [
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    "id": "ab46e5a5cd0ac998140f92af67619845a3d10509",
    "author": "Nicole Erler <NErler@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Merge pull request #34 from NErler/vignette-fix\n\nVignette fix",
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    "name": "Nicole S. Erler",
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    "description": "Assistant Professor Biostatistics\n    \n",
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    "generalized-linear-models",
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    "imputation",
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    "extra/citation.json",
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  "_realowner": "nerler",
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  "_exports": [
    "add_samples",
    "auto_corr",
    "auto_corr_plot",
    "betamm_imp",
    "betareg_imp",
    "bs",
    "clean_survname",
    "clm_imp",
    "clmm_imp",
    "coxph_imp",
    "cross_corr",
    "cross_corr_plot",
    "default_hyperpars",
    "densplot",
    "extract_state",
    "get_MIdat",
    "get_missinfo",
    "glm_imp",
    "glme_imp",
    "glmer_imp",
    "GR_crit",
    "JM_imp",
    "list_models",
    "lm_imp",
    "lme_imp",
    "lmer_imp",
    "lognorm_imp",
    "lognormmm_imp",
    "MC_error",
    "md_pattern",
    "mlogit_imp",
    "mlogitmm_imp",
    "ns",
    "parameters",
    "plot_all",
    "plot_imp_distr",
    "predDF",
    "rd_vcov",
    "set_refcat",
    "sum_duration",
    "Surv",
    "survreg_imp",
    "traceplot"
  ],
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      "name": "longDF",
      "title": "Longitudinal example dataset",
      "object": "longDF",
      "class": [
        "data.frame"
      ],
      "fields": [
        "C1",
        "C2",
        "B1",
        "B2",
        "M1",
        "M2",
        "O1",
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        "P2",
        "c1",
        "c2",
        "b1",
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        "o1",
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        "p2",
        "id",
        "time",
        "y"
      ],
      "rows": 329,
      "table": true,
      "tojson": true
    },
    {
      "name": "NHANES",
      "title": "National Health and Nutrition Examination Survey (NHANES) Data",
      "object": "NHANES",
      "class": [
        "data.frame"
      ],
      "fields": [
        "SBP",
        "gender",
        "age",
        "race",
        "WC",
        "alc",
        "educ",
        "creat",
        "albu",
        "uricacid",
        "bili",
        "occup",
        "smoke"
      ],
      "rows": 186,
      "table": true,
      "tojson": true
    },
    {
      "name": "PBC",
      "title": "PBC data",
      "object": "pbc",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "futime",
        "status",
        "trt",
        "age",
        "sex",
        "day",
        "ascites",
        "hepato",
        "spiders",
        "edema",
        "bili",
        "chol",
        "albumin",
        "alk.phos",
        "ast",
        "platelet",
        "protime",
        "stage",
        "copper",
        "trig"
      ],
      "rows": 1945,
      "table": true,
      "tojson": true
    },
    {
      "name": "simLong",
      "title": "Simulated Longitudinal Data in Long and Wide Format",
      "object": "simLong",
      "class": [
        "data.frame"
      ],
      "fields": [
        "GESTBIR",
        "ETHN",
        "AGE_M",
        "HEIGHT_M",
        "PARITY",
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      "rows": 2400,
      "table": true,
      "tojson": true
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    {
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      "object": "simWide",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "HEIGHT_M",
        "PARITY",
        "SMOKE",
        "EDUC",
        "MARITAL",
        "ID",
        "age1",
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        "sleep1",
        "age2",
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        "hc2",
        "hgt2",
        "wgt2",
        "sleep2",
        "age3",
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        "wgt3",
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        "age4",
        "bmi4",
        "hc4",
        "hgt4",
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        "sleep4",
        "age7",
        "bmi7",
        "hc7",
        "hgt7",
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        "bmi11",
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        "hgt11",
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        "sleep15",
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        "bmi26",
        "hc26",
        "hgt26",
        "wgt26",
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        "age32",
        "bmi32",
        "hc32",
        "hgt32",
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        "sleep32",
        "age40",
        "bmi40",
        "hc40",
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        "wgt40",
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        "age50",
        "bmi50",
        "hc50",
        "hgt50",
        "wgt50",
        "sleep50"
      ],
      "rows": 200,
      "table": true,
      "tojson": true
    },
    {
      "name": "wideDF",
      "title": "Cross-sectional example dataset",
      "object": "wideDF",
      "class": [
        "data.frame"
      ],
      "fields": [
        "C1",
        "C2",
        "B1",
        "B2",
        "M1",
        "M2",
        "O1",
        "O2",
        "L1",
        "L2",
        "id",
        "time",
        "y"
      ],
      "rows": 100,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "add_samples",
      "title": "Continue sampling from an object of class JointAI",
      "topics": [
        "add_samples"
      ]
    },
    {
      "page": "auto_corr",
      "title": "Autocorrelation of MCMC samples",
      "topics": [
        "auto_corr",
        "auto_corr_plot"
      ]
    },
    {
      "page": "clean_survname",
      "title": "Convert a survival outcome to a model name",
      "topics": [
        "clean_survname"
      ]
    },
    {
      "page": "cross_corr",
      "title": "Cross-correlation of MCMC samples",
      "topics": [
        "cross_corr",
        "cross_corr_plot"
      ]
    },
    {
      "page": "default_hyperpars",
      "title": "Get the default values for hyper-parameters",
      "topics": [
        "default_hyperpars"
      ]
    },
    {
      "page": "densplot",
      "title": "Plot the posterior density from object of class JointAI",
      "topics": [
        "densplot",
        "densplot.JointAI"
      ]
    },
    {
      "page": "extract_state",
      "title": "Return the current state of a 'JointAI' model",
      "topics": [
        "extract_state"
      ]
    },
    {
      "page": "get_MIdat",
      "title": "Extract multiple imputed datasets from an object of class JointAI",
      "topics": [
        "get_MIdat"
      ]
    },
    {
      "page": "get_missinfo",
      "title": "Obtain a summary of the missing values involved in an object of class JointAI",
      "topics": [
        "get_missinfo"
      ]
    },
    {
      "page": "GR_crit",
      "title": "Gelman-Rubin criterion for convergence",
      "topics": [
        "GR_crit"
      ]
    },
    {
      "page": "internal_clean_survname",
      "title": "Convert a survival outcome to a model name",
      "topics": [
        "internal_clean_survname"
      ]
    },
    {
      "page": "JointAI",
      "title": "JointAI: Joint Analysis and Imputation of Incomplete Data",
      "topics": [
        "JointAI-package",
        "JointAI"
      ]
    },
    {
      "page": "JointAIObject",
      "title": "Fitted object of class 'JointAI'",
      "topics": [
        "JointAIObject"
      ]
    },
    {
      "page": "list_models",
      "title": "List model details",
      "topics": [
        "list_models"
      ]
    },
    {
      "page": "longDF",
      "title": "Longitudinal example dataset",
      "topics": [
        "longDF"
      ]
    },
    {
      "page": "MC_error",
      "title": "Calculate and plot the Monte Carlo error",
      "topics": [
        "MC_error",
        "plot.MCElist"
      ]
    },
    {
      "page": "md_pattern",
      "title": "Missing data pattern",
      "topics": [
        "md_pattern"
      ]
    },
    {
      "page": "model_imp",
      "title": "Joint Analysis and Imputation of incomplete data",
      "topics": [
        "betamm_imp",
        "betareg_imp",
        "clmm_imp",
        "clm_imp",
        "coxph_imp",
        "glmer_imp",
        "glme_imp",
        "glm_imp",
        "JM_imp",
        "lmer_imp",
        "lme_imp",
        "lm_imp",
        "lognormmm_imp",
        "lognorm_imp",
        "mlogitmm_imp",
        "mlogit_imp",
        "model_imp",
        "survreg_imp"
      ]
    },
    {
      "page": "NHANES",
      "title": "National Health and Nutrition Examination Survey (NHANES) Data",
      "topics": [
        "NHANES"
      ]
    },
    {
      "page": "parameters",
      "title": "Parameter names of an JointAI object",
      "topics": [
        "parameters"
      ]
    },
    {
      "page": "PBC",
      "title": "PBC data",
      "topics": [
        "PBC"
      ]
    },
    {
      "page": "plot_all",
      "title": "Visualize the distribution of all variables in the dataset",
      "topics": [
        "plot_all"
      ]
    },
    {
      "page": "plot_imp_distr",
      "title": "Plot the distribution of observed and imputed values",
      "topics": [
        "plot_imp_distr"
      ]
    },
    {
      "page": "plot.JointAI",
      "title": "Plot an object object inheriting from class 'JointAI'",
      "topics": [
        "plot.JointAI"
      ]
    },
    {
      "page": "predict.JointAI",
      "title": "Predict values from an object of class JointAI",
      "topics": [
        "predict.JointAI"
      ]
    },
    {
      "page": "summary.JointAI",
      "title": "Summarize the results from an object of class JointAI",
      "topics": [
        "coef.JointAI",
        "confint.JointAI",
        "print.Dmat",
        "print.JointAI",
        "print.summary.JointAI",
        "summary.JointAI"
      ]
    },
    {
      "page": "rd_vcov",
      "title": "Extract the random effects variance covariance matrix",
      "topics": [
        "rd_vcov"
      ]
    },
    {
      "page": "residuals.JointAI",
      "title": "Extract residuals from an object of class JointAI",
      "topics": [
        "residuals.JointAI"
      ]
    },
    {
      "page": "set_refcat",
      "title": "Specify reference categories for all categorical covariates in the model",
      "topics": [
        "set_refcat"
      ]
    },
    {
      "page": "sharedParams",
      "title": "Parameters used by several functions in JointAI",
      "topics": [
        "sharedParams"
      ]
    },
    {
      "page": "simLong",
      "title": "Simulated Longitudinal Data in Long and Wide Format",
      "topics": [
        "simLong",
        "simWide"
      ]
    },
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