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  "Title": "Nonparametric Analysis of Clustered Multistate Processes",
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  "Authors@R": "person(given = \"Giorgos\",\nfamily = \"Bakoyannis\",\nrole = c(\"aut\", \"cre\"),\nemail = \"gbakogia@iu.edu\",\ncomment = c(ORCID = \"0000-0002-2789-2497\"))",
  "Description": "Nonparametric estimation of population-averaged transition\nprobabilities, with cluster-bootstrap pointwise confidence\nintervals, simultaneous confidence bands, and two-sample\nKolmogorov-Smirnov-type tests for clustered or independent\nmultistate process data. Estimation follows Bakoyannis (2021)\n<doi:10.1111/biom.13327>; two-sample inference for the\ncluster-randomized and independent-samples designs follows\nBakoyannis and Bandyopadhyay (2022)\n<doi:10.1007/s10463-021-00819-x>. Both methods use the\nworking-independence Aalen-Johansen estimator. The package\nsupports both progressive (acyclic) and non-monotone (e.g.,\nillness-death with recovery) multistate processes, right\ncensoring, left truncation, and informative cluster size. The\nuser supplies data in interval format (one row per\nmutually-exclusive time interval per subject) and interacts\nwith the package through a single formula-based function,\npatp().",
  "License": "GPL-3",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/gbakoyannis/clusteredMSM",
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  "Date/Publication": "2026-05-20 02:02:38 UTC",
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    "User": "root"
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  "Author": "Giorgos Bakoyannis [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-2789-2497>)",
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    "author": "Giorgos Bakoyannis <gbakogia@iu.edu>",
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    "message": "Update cran-comments.md for resubmission\n\nDocument the win-builder R-devel run (2026-05-20: 0 errors, 0\nwarnings, 1 NOTE), respond to the reviewer's \\dontrun{} comment\n(all examples unwrapped; none needed \\donttest{}), and describe\nthe single NOTE as the standard new-submission flag plus the\nintentional proper-noun/domain-term spellings. Calibration\nsimulation summary retained.\n\nCo-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>\n",
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  "_topics": [
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    "clustered-data",
    "multistate-models",
    "nonparametric-statistics",
    "survival-analysis"
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      "title": "Synthetic Clustered Illness-Death-with-Recovery Data",
      "object": "example_msm",
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    },
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      "title": "Generic Cluster Bootstrap Engine",
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    },
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      ]
    },
    {
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      "title": "Construct a Multistate Interval Object for Use in patp() Formulas",
      "topics": [
        "msm"
      ]
    },
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      "title": "Population-Averaged Transition Probabilities for Multistate Process Data",
      "topics": [
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      "title": "Print Method for patp Objects",
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      "title": "Aalen-Johansen Product Integral for General Multistate Processes",
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