{
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  "Package": "alphaN",
  "Title": "Set Alpha Based on Sample Size Using Bayes Factors",
  "Version": "0.2.0.9000",
  "Authors@R": "c(\nperson(\"Jesper\", \"Wulff\", , \"jwulff@econ.au.dk\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-7976-0939\")),\nperson(\"Luke\", \"Taylor\", , \"lntaylor@econ.au.dk\", role = \"aut\")\n)",
  "Description": "Sets the alpha level for coefficients in a regression\nmodel as a decreasing function of the sample size through the\nuse of Jeffreys' Approximate Bayes factor. You tell alphaN()\nyour sample size, and it tells you to which value you must\nlower alpha to avoid Lindley's Paradox. For details, see Wulff\nand Taylor (2024) <doi:10.1177/14761270231214429>. Alpha can\nalso be calibrated to the effect-size and moment Bayes factors\nof Klauer, Meyer-Grant, and Kellen (2025)\n<doi:10.3758/s13423-024-02612-2>, which center the alternative\nhypothesis on an effect size of your choosing.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/jespernwulff/alphaN,\nhttps://jespernwulff.github.io/alphaN/",
  "BugReports": "https://github.com/jespernwulff/alphaN/issues",
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  "Repository": "https://jespernwulff.r-universe.dev",
  "Date/Publication": "2026-07-23 08:26:09 UTC",
  "RemoteUrl": "https://github.com/jespernwulff/alphan",
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  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
  },
  "Author": "Jesper Wulff [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-7976-0939>),\nLuke Taylor [aut]",
  "Maintainer": "Jesper Wulff <jwulff@econ.au.dk>",
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  "_created": "2026-07-23T11:05:55.000Z",
  "_published": "2026-07-23T11:13:00.505Z",
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    "author": "Jesper Wulff <jespernydamwulff@gmail.com>",
    "committer": "Jesper Wulff <jespernydamwulff@gmail.com>",
    "message": "README: showcase the development-version features\n\nPower at the calibrated alpha (alphaN_power, alphaN_power_plot with the\ntwo-panel figure, pwrss bridge), the preregistration-ready settings\nreport (with Scope line and power_at), JAB() all-coefficients mode, and\na note marking which sections need the GitHub install until 0.3.0.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>\n",
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      "date": "2026-07-11"
    }
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  "_contributors": [
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    "name": "Jesper N. Wulff",
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    "extra/citation.cff",
    "extra/citation.html",
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    "extra/citation.txt",
    "extra/contents.json",
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    "extra/readme.md",
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  "_realowner": "jespernwulff",
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      "date": "2023-01-14"
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      "date": "2025-07-13"
    },
    {
      "version": "0.2.0",
      "date": "2026-07-12"
    }
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    "alphaN",
    "alphaN_plot",
    "alphaN_power",
    "alphaN_power_plot",
    "alphaN_report",
    "JAB",
    "JAB_plot",
    "JABp",
    "JABt",
    "klauerBF",
    "n_effective"
  ],
  "_help": [
    {
      "page": "alphaN",
      "title": "Set the alpha level based on sample size for coefficients in a regression model",
      "topics": [
        "alphaN"
      ]
    },
    {
      "page": "alphaN_plot",
      "title": "Creates a plot of alpha as function of sample size for the chosen methods",
      "topics": [
        "alphaN_plot"
      ]
    },
    {
      "page": "alphaN_power",
      "title": "Power at the calibrated alpha level",
      "topics": [
        "alphaN_power"
      ]
    },
    {
      "page": "alphaN_power_plot",
      "title": "Plot power across sample sizes at the calibrated alpha",
      "topics": [
        "alphaN_power_plot"
      ]
    },
    {
      "page": "alphaN_report",
      "title": "Write a settings report for a calibrated alpha level",
      "topics": [
        "alphaN_report"
      ]
    },
    {
      "page": "JAB",
      "title": "Transforms t-statistics from a glm or lm object into Jeffreys' approximate Bayes factors",
      "topics": [
        "JAB"
      ]
    },
    {
      "page": "JAB_plot",
      "title": "Plots JAB as a function of the p-value",
      "topics": [
        "JAB_plot"
      ]
    },
    {
      "page": "JABp",
      "title": "Transforms a p-value into Jeffreys' approximate Bayes factor",
      "topics": [
        "JABp"
      ]
    },
    {
      "page": "JABt",
      "title": "Transforms a t-statistic into Jeffreys' approximate Bayes factor",
      "topics": [
        "JABt"
      ]
    },
    {
      "page": "klauerBF",
      "title": "Effect-size or moment Bayes factor from a t or F statistic",
      "topics": [
        "klauerBF"
      ]
    },
    {
      "page": "n_effective",
      "title": "Effective sample size from cluster-robust standard errors",
      "topics": [
        "n_effective"
      ]
    }
  ],
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      "title": "Intro to alphaN",
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      "headings": [
        "Installation",
        "Basic functionality",
        "Setting the alpha level",
        "Plotting the relationship between the Bayes factor and p-value",
        "Alpha as a decreasing function of N",
        "Setting the prior",
        "Calibrating alpha to effect-size and moment Bayes factors",
        "Bayes factors, joint tests, and clustered data"
      ],
      "created": "2023-01-03 12:42:12",
      "modified": "2026-07-16 19:32:06",
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