{
  "_id": "6a27d88724555f66ed546b58",
  "Package": "CIMEHR",
  "Title": "Gaussian Clinically Informative Visiting and Observation\nProcesses in Electronic Health Record (EHR) Data",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(given = \"Cheng-Han\", family = \"Yang\",\nemail = \"chenghanyang728@gmail.com\",\nrole = c(\"aut\",\"cre\"),\ncomment = c(ORCID = \"0000-0002-4161-3140\")),\nperson(given = \"Yiren\", family = \"Hou\",\nemail = \"yiren.hou@yale.edu\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0009-0005-0422-4268\"))\n)",
  "Description": "Fits semiparametric joint models for longitudinal\nelectronic health record (EHR) data that addresses two-stage\nhierarchical missingness mechanism. The first stage is the\nvisiting process, and the second stage is the observation\nprocess. The core CIMEHR method (Clinical Informative\nMissingness for Electronic Health Records) uses a three-stage\nprocedure: partial likelihood with log-normal frailty for visit\nintensity, probit regression with shared latent factor-linked\nrandom effects for observation, and weighted least squares with\nrisk-set centering for the outcome. These three stages are\nconnected through a shared latent factor that induces\ndependence across all three processes. A data simulator and\nimplementations of common benchmark methods (linear mixed\nmodels, multiple imputation, and others) are included for\ncomparative studies. Detailed methods are described in Yang,\nShi, and Mukherjee (2026) <doi:10.48550/arXiv.2602.15374>.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.3",
  "URL": "https://github.com/ysph-dsde/CIMEHR",
  "BugReports": "https://github.com/ysph-dsde/CIMEHR/issues",
  "VignetteBuilder": "knitr",
  "LazyData": "true",
  "Config/pak/sysreqs": "cmake make libicu-dev libx11-dev zlib1g-dev",
  "Repository": "https://ysph-dsde.r-universe.dev",
  "Date/Publication": "2026-06-02 14:58:53 UTC",
  "RemoteUrl": "https://github.com/ysph-dsde/cimehr",
  "RemoteRef": "HEAD",
  "RemoteSha": "62c978710930a7248d2849aed64dbc15a27cba3b",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-09 09:04:09 UTC",
    "User": "root"
  },
  "Author": "Cheng-Han Yang [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-4161-3140>),\nYiren Hou [aut] (ORCID: <https://orcid.org/0009-0005-0422-4268>)",
  "Maintainer": "Cheng-Han Yang <chenghanyang728@gmail.com>",
  "MD5sum": "62b13a84135487bf55053a46aadefd9b",
  "_user": "ysph-dsde",
  "_type": "src",
  "_file": "CIMEHR_0.1.0.tar.gz",
  "_fileid": "35e0d3b4571ad6ba86b36fc756770d5a56f33e05ebad0424f6da8a22a68fc605",
  "_filesize": 1214825,
  "_sha256": "35e0d3b4571ad6ba86b36fc756770d5a56f33e05ebad0424f6da8a22a68fc605",
  "_created": "2026-06-09T09:04:09.000Z",
  "_published": "2026-06-09T09:10:31.018Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 80286479658,
      "time": 148,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7503249913"
    },
    {
      "job": 80286479641,
      "time": 134,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7503243176"
    },
    {
      "job": 80286479685,
      "time": 150,
      "config": "linux-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503251271"
    },
    {
      "job": 80286479639,
      "time": 141,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503246498"
    },
    {
      "job": 80286479753,
      "time": 205,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7503260767"
    },
    {
      "job": 80286479661,
      "time": 239,
      "config": "macos-oldrel-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7503276372"
    },
    {
      "job": 80286479680,
      "time": 211,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503259898"
    },
    {
      "job": 80286479779,
      "time": 326,
      "config": "macos-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503297116"
    },
    {
      "job": 80285600621,
      "time": 285,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503190544"
    },
    {
      "job": 80286479603,
      "time": 121,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503238405"
    },
    {
      "job": 80286479645,
      "time": 112,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7503234971"
    },
    {
      "job": 80286479699,
      "time": 110,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7503234052"
    },
    {
      "job": 80286479648,
      "time": 108,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7503233583"
    }
  ],
  "_buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/ysph-dsde/cimehr",
  "_commit": {
    "id": "62c978710930a7248d2849aed64dbc15a27cba3b",
    "author": "yirenhou2001 <hou.yiren@gmail.com>",
    "committer": "yirenhou2001 <hou.yiren@gmail.com>",
    "message": "Updates before first submission to CRAN\n",
    "time": 1780412333
  },
  "_maintainer": {
    "name": "Cheng-Han Yang",
    "email": "chenghanyang728@gmail.com",
    "login": "cyang728",
    "description": "I am an Associate Research Sciesntist in Biostatistics program at Yale university. My research interests lie in EHR data analysis and survival analysis. ",
    "uuid": 97812515,
    "orcid": "0000-0002-4161-3140"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.5",
      "role": "Depends"
    },
    {
      "package": "Rcpp",
      "role": "LinkingTo"
    },
    {
      "package": "MASS",
      "role": "Imports"
    },
    {
      "package": "Rcpp",
      "role": "Imports"
    },
    {
      "package": "nleqslv",
      "role": "Imports"
    },
    {
      "package": "pbivnorm",
      "role": "Imports"
    },
    {
      "package": "numDeriv",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "data.table",
      "role": "Imports"
    },
    {
      "package": "mice",
      "role": "Imports"
    },
    {
      "package": "nlme",
      "role": "Imports"
    },
    {
      "package": "slim",
      "role": "Imports"
    },
    {
      "package": "tibble",
      "role": "Suggests"
    },
    {
      "package": "dplyr",
      "role": "Suggests"
    },
    {
      "package": "tidyr",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "ysph-dsde",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-10",
      "n": 9
    },
    {
      "week": "2026-13",
      "n": 5
    },
    {
      "week": "2026-17",
      "n": 5
    },
    {
      "week": "2026-18",
      "n": 14
    },
    {
      "week": "2026-19",
      "n": 5
    },
    {
      "week": "2026-21",
      "n": 13
    },
    {
      "week": "2026-22",
      "n": 2
    },
    {
      "week": "2026-23",
      "n": 1
    }
  ],
  "_tags": [],
  "_stars": 0,
  "_contributors": [
    {
      "user": "yirenhou2001",
      "count": 54,
      "uuid": 214887223
    }
  ],
  "_userbio": {
    "uuid": 184402761,
    "type": "organization",
    "name": "YSPH Data Science and Data Equity"
  },
  "_downloads": {
    "count": 0,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/CIMEHR"
  },
  "_devurl": "https://github.com/ysph-dsde/cimehr",
  "_searchresults": 0,
  "_topics": [
    "cpp"
  ],
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/CIMEHR.html",
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/ysph-dsde/cimehr",
  "_realowner": "ysph-dsde",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.1.0",
      "date": "2026-06-08"
    }
  ],
  "_exports": [
    "available_comparison_methods",
    "bootstrap",
    "CIMEHR",
    "CIMEHR_timevarying_integral",
    "CIMEHR_timevarying_ou",
    "coef_stage",
    "EHRJoint",
    "extract_coefficient",
    "Inverse_intensity_rate_ratio_balancing",
    "Inverse_intensity_rate_ratio_weighting",
    "Joint_modeling_visiting_and_longitudinal_Liang",
    "Linear_increment",
    "Linear_increment_IP",
    "Linear_mixed_model",
    "method_comparisons",
    "Multiple_imputation",
    "Multiple_imputation_IP",
    "Pairwise_likelihood",
    "sim_data_gen",
    "summary_observation",
    "summary_outcome",
    "Summary_stat",
    "summary_visiting"
  ],
  "_datasets": [
    {
      "name": "sim_ehr_data",
      "title": "Simulated Electronic Health Record (EHR) Longitudinal Data",
      "object": "sim_ehr_data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "Age",
        "Gender",
        "Marital",
        "Black",
        "Hispanic",
        "NSES",
        "time",
        "R",
        "log_HbA1c",
        "C"
      ],
      "rows": 16945,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "available_comparison_methods",
      "title": "Available Methods for method_comparisons()",
      "topics": [
        "available_comparison_methods"
      ]
    },
    {
      "page": "bootstrap",
      "title": "Bootstrap Confidence Intervals for Selected Model Fits",
      "topics": [
        "bootstrap"
      ]
    },
    {
      "page": "CIMEHR",
      "title": "Clinical Informative Missingness for Electronic Health Records (CIMEHR) - Joint Three-Stage Model",
      "topics": [
        "CIMEHR"
      ]
    },
    {
      "page": "CIMEHR_timevarying_integral",
      "title": "Clinical Informative Missingness for Electronic Health Records (CIMEHR) with Gauss-Hermite (GH) Quadrature - Time-Varying Variant",
      "topics": [
        "CIMEHR_timevarying_integral"
      ]
    },
    {
      "page": "CIMEHR_timevarying_ou",
      "title": "Clinical Informative Missingness for Electronic Health Records (CIMEHR) with Ornstein-Uhlenbeck (OU) Pairwise Composite Likelihood (PCL) Extension - Time-Varying Variant",
      "topics": [
        "CIMEHR_timevarying_ou"
      ]
    },
    {
      "page": "coef.CIMEHR",
      "title": "Extract Coefficients from a Clinical Informative Missingness for Electronic Health Records (CIMEHR) Fit",
      "topics": [
        "coef.CIMEHR",
        "coef.CIMEHR_timevarying_integral",
        "coef.CIMEHR_timevarying_ou"
      ]
    },
    {
      "page": "confint.CIMEHR",
      "title": "Confidence Intervals for Clinical Informative Missingness for Electronic Health Records (CIMEHR) Outcome Coefficients",
      "topics": [
        "confint.CIMEHR",
        "confint.CIMEHR_timevarying_ou"
      ]
    },
    {
      "page": "EHRJoint",
      "title": "Joint Estimation for Electronic Health Record (EHR) Longitudinal Processes (EHRJoint)",
      "topics": [
        "EHRJoint"
      ]
    },
    {
      "page": "extract_coefficient",
      "title": "Extract One or More Coefficients from a Fitted Method",
      "topics": [
        "coef_stage",
        "extract_coefficient"
      ]
    },
    {
      "page": "Inverse_intensity_rate_ratio_balancing",
      "title": "Inverse Intensity Rate Ratio (IIRR) Estimator with Balancing Weights",
      "topics": [
        "Inverse_intensity_rate_ratio_balancing"
      ]
    },
    {
      "page": "Inverse_intensity_rate_ratio_weighting",
      "title": "Inverse Intensity Rate Ratio (IIRR) Weighting Estimator",
      "topics": [
        "Inverse_intensity_rate_ratio_weighting"
      ]
    },
    {
      "page": "Joint_modeling_visiting_and_longitudinal_Liang",
      "title": "Joint Model for Visiting and Longitudinal (JMVL) Processes with Informative Presence (IP) Adjustment (Liang's Method)",
      "topics": [
        "Joint_modeling_visiting_and_longitudinal_Liang"
      ]
    },
    {
      "page": "Linear_increment_IP",
      "title": "Linear Increment (LI) Imputation with Informative Presence (IP) Adjustment",
      "topics": [
        "Linear_increment_IP"
      ]
    },
    {
      "page": "Linear_mixed_model",
      "title": "Fit a Linear Mixed Model for Longitudinal Data",
      "topics": [
        "Linear_mixed_model"
      ]
    },
    {
      "page": "method_comparisons",
      "title": "Fit and Compare Multiple Methods",
      "topics": [
        "Linear_increment",
        "method_comparisons",
        "Multiple_imputation"
      ]
    },
    {
      "page": "Multiple_imputation_IP",
      "title": "Multiple Imputation (MI) with Informative Presence (IP) Adjustment",
      "topics": [
        "Multiple_imputation_IP"
      ]
    },
    {
      "page": "Pairwise_likelihood",
      "title": "Pairwise Composite Likelihood (PCL) Generalized Linear Model (GLM) Estimation",
      "topics": [
        "Pairwise_likelihood"
      ]
    },
    {
      "page": "print.CIMEHR",
      "title": "Print a Clinical Informative Missingness for Electronic Health Records (CIMEHR) Fit",
      "topics": [
        "print.CIMEHR"
      ]
    },
    {
      "page": "print.cimehr_bootstrap",
      "title": "Print a Bootstrap Result",
      "topics": [
        "print.cimehr_bootstrap"
      ]
    },
    {
      "page": "print.CIMEHR_timevarying_integral",
      "title": "Print a Clinical Informative Missingness for Electronic Health Records with Gauss-Hermite Quadrature (CIMEHR_timevarying_integral) Fit",
      "topics": [
        "print.CIMEHR_timevarying_integral"
      ]
    },
    {
      "page": "print.CIMEHR_timevarying_ou",
      "title": "Print a Clinical Informative Missingness for Electronic Health Records with Ornstein-Uhlenbeck Pairwise Composite Likelihood (CIMEHR_timevarying_ou) Fit",
      "topics": [
        "print.CIMEHR_timevarying_ou"
      ]
    },
    {
      "page": "print.EHRJoint",
      "title": "Print a Joint Estimation for Electronic Health Record (EHR) Longitudinal Processes (EHRJoint) Fit",
      "topics": [
        "print.EHRJoint"
      ]
    },
    {
      "page": "print.Inverse_intensity_rate_ratio_balancing",
      "title": "Print an Inverse Intensity Rate Ratio (IIRR) Estimator with Balancing Weights Fit",
      "topics": [
        "print.Inverse_intensity_rate_ratio_balancing"
      ]
    },
    {
      "page": "print.Inverse_intensity_rate_ratio_weighting",
      "title": "Print an Inverse Intensity Rate Ratio (IIRR) Weighting Estimator Fit",
      "topics": [
        "print.Inverse_intensity_rate_ratio_weighting"
      ]
    },
    {
      "page": "print.Joint_modeling_visiting_and_longitudinal_Liang",
      "title": "Print a Joint Model for Visiting and Longitudinal (JMVL) Processes (Liang) Fit",
      "topics": [
        "print.Joint_modeling_visiting_and_longitudinal_Liang"
      ]
    },
    {
      "page": "print.Linear_increment_IP_result",
      "title": "Print a Linear Increment (LI) Imputation with Informative Presence (IP) Adjustment Fit",
      "topics": [
        "print.Linear_increment_IP_result"
      ]
    },
    {
      "page": "print.Linear_mixed_model_result",
      "title": "Print a Linear Mixed Model for Longitudinal Data Result",
      "topics": [
        "print.Linear_mixed_model_result"
      ]
    },
    {
      "page": "print.Multiple_imputation_IP_result",
      "title": "Print a Multiple Imputation (MI) with Informative Presence (IP) Adjustment Fit",
      "topics": [
        "print.Multiple_imputation_IP_result"
      ]
    },
    {
      "page": "print.Pairwise_likelihood",
      "title": "Print a Pairwise Composite Likelihood (PCL) Generalized Linear Model (Pairwise_likelihood) Fit",
      "topics": [
        "print.Pairwise_likelihood"
      ]
    },
    {
      "page": "print.Summary_stat_result",
      "title": "Print a Summary-Statistic Regression for Longitudinal Data Result",
      "topics": [
        "print.Summary_stat_result"
      ]
    },
    {
      "page": "sim_data_gen",
      "title": "Simulate Longitudinal Electronic Health Record (EHR) Data with Informative Visiting and Observation Processes",
      "topics": [
        "sim_data_gen"
      ]
    },
    {
      "page": "sim_ehr_data",
      "title": "Simulated Electronic Health Record (EHR) Longitudinal Data",
      "topics": [
        "sim_ehr_data"
      ]
    },
    {
      "page": "summary_observation",
      "title": "Summarise the Observation Process of a Fitted Method",
      "topics": [
        "summary_observation"
      ]
    },
    {
      "page": "summary_outcome",
      "title": "Summarise the Outcome Process of a Fitted Method",
      "topics": [
        "summary_outcome"
      ]
    },
    {
      "page": "Summary_stat",
      "title": "Summary-Statistic Regression for Longitudinal Data",
      "topics": [
        "Summary_stat"
      ]
    },
    {
      "page": "summary_visiting",
      "title": "Summarise the Visiting Process of a Fitted Method",
      "topics": [
        "summary_visiting"
      ]
    },
    {
      "page": "summary.CIMEHR",
      "title": "Summarise a Clinical Informative Missingness for Electronic Health Records (CIMEHR) Fit",
      "topics": [
        "summary.CIMEHR"
      ]
    },
    {
      "page": "summary.cimehr_bootstrap",
      "title": "Summarise a Bootstrap Result",
      "topics": [
        "summary.cimehr_bootstrap"
      ]
    },
    {
      "page": "summary.CIMEHR_timevarying_integral",
      "title": "Summarise a Clinical Informative Missingness for Electronic Health Records with Gauss-Hermite Quadrature (CIMEHR_timevarying_integral) Fit",
      "topics": [
        "summary.CIMEHR_timevarying_integral"
      ]
    },
    {
      "page": "summary.CIMEHR_timevarying_ou",
      "title": "Summarise a Clinical Informative Missingness for Electronic Health Records with Ornstein-Uhlenbeck Pairwise Composite Likelihood (CIMEHR_timevarying_ou) Fit",
      "topics": [
        "summary.CIMEHR_timevarying_ou"
      ]
    },
    {
      "page": "summary.EHRJoint",
      "title": "Summarise a Joint Estimation for Electronic Health Record (EHR) Longitudinal Processes (EHRJoint) Fit",
      "topics": [
        "summary.EHRJoint"
      ]
    },
    {
      "page": "summary.Inverse_intensity_rate_ratio_balancing",
      "title": "Summarise an Inverse Intensity Rate Ratio (IIRR) Estimator with Balancing Weights Fit",
      "topics": [
        "summary.Inverse_intensity_rate_ratio_balancing"
      ]
    },
    {
      "page": "summary.Inverse_intensity_rate_ratio_weighting",
      "title": "Summarise an Inverse Intensity Rate Ratio (IIRR) Weighting Estimator Fit",
      "topics": [
        "summary.Inverse_intensity_rate_ratio_weighting"
      ]
    },
    {
      "page": "summary.Joint_modeling_visiting_and_longitudinal_Liang",
      "title": "Summarise a Joint Model for Visiting and Longitudinal (JMVL) Processes (Liang) Fit",
      "topics": [
        "summary.Joint_modeling_visiting_and_longitudinal_Liang"
      ]
    },
    {
      "page": "summary.Linear_increment_IP_result",
      "title": "Summarise a Linear Increment (LI) Imputation with Informative Presence (IP) Adjustment Fit",
      "topics": [
        "summary.Linear_increment_IP_result"
      ]
    },
    {
      "page": "summary.Linear_mixed_model_result",
      "title": "Summarise a Linear Mixed Model for Longitudinal Data Result",
      "topics": [
        "summary.Linear_mixed_model_result"
      ]
    },
    {
      "page": "summary.Multiple_imputation_IP_result",
      "title": "Summarise a Multiple Imputation (MI) with Informative Presence (IP) Adjustment Fit",
      "topics": [
        "summary.Multiple_imputation_IP_result"
      ]
    },
    {
      "page": "summary.Pairwise_likelihood",
      "title": "Summarise a Pairwise Composite Likelihood (PCL) Generalized Linear Model (Pairwise_likelihood) Fit",
      "topics": [
        "summary.Pairwise_likelihood"
      ]
    },
    {
      "page": "summary.Summary_stat_result",
      "title": "Summarise a Summary-Statistic Regression for Longitudinal Data Result",
      "topics": [
        "summary.Summary_stat_result"
      ]
    },
    {
      "page": "vcov.CIMEHR",
      "title": "Variance-Covariance Matrix for Clinical Informative Missingness for Electronic Health Records (CIMEHR) Outcome Coefficients",
      "topics": [
        "vcov.CIMEHR",
        "vcov.CIMEHR_timevarying_ou"
      ]
    }
  ],
  "_readme": "https://github.com/ysph-dsde/cimehr/raw/HEAD/README.md",
  "_rundeps": [
    "backports",
    "bit",
    "bit64",
    "boot",
    "broom",
    "cli",
    "clipr",
    "codetools",
    "cpp11",
    "crayon",
    "data.table",
    "dplyr",
    "forcats",
    "foreach",
    "generics",
    "glmnet",
    "glue",
    "haven",
    "hms",
    "iterators",
    "jomo",
    "lattice",
    "lifecycle",
    "lme4",
    "magrittr",
    "MASS",
    "Matrix",
    "mice",
    "minqa",
    "mitml",
    "nleqslv",
    "nlme",
    "nloptr",
    "nnet",
    "numDeriv",
    "ordinal",
    "pan",
    "pbivnorm",
    "pillar",
    "pkgconfig",
    "prettyunits",
    "progress",
    "purrr",
    "R6",
    "rbibutils",
    "Rcpp",
    "RcppEigen",
    "Rdpack",
    "readr",
    "reformulas",
    "rlang",
    "rpart",
    "shape",
    "slim",
    "stringi",
    "stringr",
    "survival",
    "tibble",
    "tidyr",
    "tidyselect",
    "tzdb",
    "ucminf",
    "utf8",
    "vctrs",
    "vroom",
    "withr"
  ],
  "_sysdeps": [
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_vignettes": [
    {
      "source": "getting-started.Rmd",
      "filename": "getting-started.html",
      "title": "Getting Started with CIMEHR",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "1. Input data format",
        "1.1 Converting short/wide data to long data",
        "2. Example dataset",
        "3. Method comparison",
        "Methods implemented in CIMEHR",
        "Outcome-only",
        "IP-only",
        "Imputation + IP-only",
        "IP+IO",
        "4. Simpler benchmark methods first",
        "4.1 Summary-statistic regression",
        "4.2 Linear mixed model",
        "4.3 Pairwise likelihood",
        "5. Visiting-process and joint methods",
        "5.1 Inverse intensity rate ratio weighting",
        "5.2 Inverse intensity rate ratio balancing",
        "5.3 Liang--Lu--Ying joint visiting/outcome model",
        "5.4 EHRJoint",
        "6. Primary CIMEHR methods",
        "6.1 Base CIMEHR",
        "6.1.1 Stage-specific summaries and coefficient extraction",
        "6.2 CIMEHR with Gauss--Hermite quadrature",
        "6.3 CIMEHR with OU pairwise composite likelihood",
        "7. Comparing methods with method_comparisons()",
        "8. Simulation study",
        "9. Bootstrap inference",
        "10. Simulating custom data",
        "References"
      ],
      "created": "2026-03-04 05:43:40",
      "modified": "2026-05-26 01:27:23",
      "commits": 33
    }
  ],
  "_score": 4.6020599913279625,
  "_indexed": true,
  "_nocasepkg": "cimehr",
  "_universes": [
    "ysph-dsde",
    "cyang728"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-06-09T09:06:51.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "dbf2546af3f2524f3e1678a61299db9bb0d4a9a9eb6a8402a4a6256d41af98e9",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-06-09T09:06:31.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "b593ed3a6c4b7c613665238b4f76bae984e324d6fe66222f70c1d566a7e3450e",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-06-09T09:06:55.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "c5905d85498b43f6ce94e96b2e687e4ab0333defe69cadf0ce31c0d7097eb8a2",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-06-09T09:06:39.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "c86494ba7d47b728799c9140e416f56671149958906aa95d93378415526b3f37",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.1.0",
      "date": "2026-06-09T09:07:13.000Z",
      "arch": "aarch64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "a74a17cdc4d4cf3d0aa27f654cc92b725f78e6b43066b41339af018992f3be78",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.1.0",
      "date": "2026-06-09T09:07:41.000Z",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "31648c8b965ab66b7fa1a2b416a95a1c7e17a63a6b8c19841c2a615b2e5ef8de",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "0.1.0",
      "date": "2026-06-09T09:07:06.000Z",
      "arch": "aarch64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "0e99996904f00e5ee2ea2afbe67bdaf9a78657c98fe096b8ce3dd1c7f0e65aca",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "0.1.0",
      "date": "2026-06-09T09:08:15.000Z",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "1d8099aa255fa47c5cf6d33f858f2d6057f58abc96488f4bf6350e4eb8afe0ec",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.1.0",
      "date": "2026-06-09T09:06:41.000Z",
      "arch": "emscripten",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "129bf940eb09380e877582a21a6d2efab095db47adeacccc9066102a43de34eb",
      "status": "success",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.1.0",
      "date": "2026-06-09T09:05:41.000Z",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "f190c98966116f0cb06f28c602785c970776a452586d8be82bbbdbfda2e73a56",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "0.1.0",
      "date": "2026-06-09T09:05:42.000Z",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "32de48e270842b69349dd45f41748bb77a67e05d34551757ead04a6b068451b0",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "0.1.0",
      "date": "2026-06-09T09:05:41.000Z",
      "arch": "x86_64",
      "commit": "62c978710930a7248d2849aed64dbc15a27cba3b",
      "fileid": "c0c88ae998e0245341f3d6173dc648c1fdc7d461f9dc59622352c56421268111",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/ysph-dsde/actions/runs/27195384280"
    }
  ]
}