{
  "_id": "6a11738bacfb0bcc41cf842f",
  "Package": "babebi",
  "Type": "Package",
  "Title": "Bayesian Estimation and Validation for Small-N Designs with\nRater Bias",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(\ngiven = \"Irene\",\nfamily = \"Gianeselli\",\nemail = \"irene.gianeselli@unibz.it\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(\nORCID = \"0000-0002-8689-3035\",\naffiliation = \"Free University of Bozen-Bolzano\"\n)\n),\nperson(\ngiven = \"Andrea\",\nfamily = \"Bosco\",\nrole = \"aut\",\ncomment = c(\nORCID = \"0000-0002-9458-3993\",\naffiliation = \"University of Bari Aldo Moro\"\n)\n),\nperson(\ngiven = \"Demis\",\nfamily = \"Basso\",\nrole = \"aut\",\ncomment = c(\nORCID = \"0000-0002-4595-3513\",\naffiliation = \"Free University of Bozen-Bolzano\"\n)\n)\n)",
  "Description": "Approximate Bayesian inference and Monte Carlo validation\nfor small-N repeated-measures designs with two time points and\ntwo raters. The package is intended for applications in which\nsample size is limited and the observed outcome may be affected\nby rater-specific bias. User-supplied data are standardised\ninto a common long-format structure. Pre-post effects are\nanalysed using difference scores in a linear model with a rater\nindicator as covariate. Posterior summaries for the regression\ncoefficients are obtained from a large-sample normal\napproximation centred at the least-squares estimate with\nplug-in covariance under a flat improper prior. Evidence for a\nnon-zero pre-post effect, adjusted for rater differences, is\nsummarised using a BIC-based approximation to the Bayes factor\nfor comparison between models with and without the pre-post\neffect. Monte Carlo validation uses design quantities estimated\nfrom the observed data, including sample size, mean pre-post\nchange, and second-rater additive discrepancy, and summarises\ninferential performance in terms of bias, root mean squared\nerror, credible interval coverage, posterior tail\nprobabilities, and mean Bayes factor values. For background on\nthe BIC approximation and Bayes factors, see Schwarz (1978)\n<doi:10.1214/aos/1176344136> and Kass and Raftery (1995)\n<doi:10.1080/01621459.1995.10476572>.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.3.3",
  "Config/testthat/edition": "3",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-23 09:26:42 UTC",
    "User": "root"
  },
  "Author": "Irene Gianeselli [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-8689-3035>, affiliation: Free\nUniversity of Bozen-Bolzano), Andrea Bosco [aut] (ORCID:\n<https://orcid.org/0000-0002-9458-3993>, affiliation:\nUniversity of Bari Aldo Moro), Demis Basso [aut] (ORCID:\n<https://orcid.org/0000-0002-4595-3513>, affiliation: Free\nUniversity of Bozen-Bolzano)",
  "Maintainer": "Irene Gianeselli <irene.gianeselli@unibz.it>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-04-23 22:05:16 UTC",
  "RemoteUrl": "https://github.com/cran/babebi",
  "RemoteRef": "HEAD",
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  "MD5sum": "1cc3f6fc16acba8908d0341f6c8eeeed",
  "_user": "cran",
  "_type": "src",
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  "_created": "2026-05-23T09:26:42.000Z",
  "_published": "2026-05-23T09:29:47.369Z",
  "_distro": "noble",
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  "_buildurl": "https://github.com/r-universe/cran/actions/runs/26329125115",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/babebi",
  "_commit": {
    "id": "aa79b08b62dd3f156631dbae2521f5000677705e",
    "author": "Irene Gianeselli <irene.gianeselli@unibz.it>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.1.0\n",
    "time": 1776981916
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  "_maintainer": {
    "name": "Irene Gianeselli",
    "email": "irene.gianeselli@unibz.it",
    "orcid": "0000-0002-8689-3035"
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  "_dependencies": [
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      "version": ">= 4.1.0",
      "role": "Depends"
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      "package": "stats",
      "role": "Imports"
    },
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      "role": "Imports"
    },
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      "version": ">= 3.0.0",
      "role": "Suggests"
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      "package": "knitr",
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  "_owner": "cran",
  "_selfowned": false,
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  "_updates": [
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  "_userbio": {
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    "type": "organization",
    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 499,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/babebi"
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  "_searchresults": 6,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "manual.pdf"
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  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
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  "_exports": [
    "babebi",
    "fit_model",
    "montecarlo_from_data"
  ],
  "_help": [
    {
      "page": "babebi",
      "title": "Run the babebi workflow on user-supplied data",
      "topics": [
        "babebi"
      ]
    },
    {
      "page": "fit_model",
      "title": "Fit the babebi model to observed data",
      "topics": [
        "fit_model"
      ]
    },
    {
      "page": "montecarlo_from_data",
      "title": "Run Monte Carlo calibration from user-supplied data",
      "topics": [
        "montecarlo_from_data"
      ]
    },
    {
      "page": "plot.babebi_fit",
      "title": "Plot a babebi fit object",
      "topics": [
        "plot.babebi_fit"
      ]
    },
    {
      "page": "print.babebi_fit",
      "title": "Print a babebi fit object",
      "topics": [
        "print.babebi_fit"
      ]
    },
    {
      "page": "print.babebi_validation",
      "title": "Print a babebi validation object",
      "topics": [
        "print.babebi_validation"
      ]
    },
    {
      "page": "print.summary.babebi_fit",
      "title": "Print a summary of a babebi fit object",
      "topics": [
        "print.summary.babebi_fit"
      ]
    },
    {
      "page": "summary.babebi_fit",
      "title": "Summarise a babebi fit object",
      "topics": [
        "summary.babebi_fit"
      ]
    }
  ],
  "_rundeps": [],
  "_score": 1,
  "_indexed": true,
  "_nocasepkg": "babebi",
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