{
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  "Package": "mmibain",
  "Title": "Bayesian Informative Hypotheses Evaluation Web Applications",
  "Version": "0.2.0.9000",
  "Authors@R": "c(\nperson(\"Mackson\", \"Ncube\", , \"macksonncube.stats@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"mightymetrika, LLC\", role = c(\"cph\", \"fnd\"))\n)",
  "Description": "Researchers often have expectations about the relations\nbetween means of different groups or standardized regression\ncoefficients; using informative hypothesis testing to\nincorporate these expectations into the analysis through order\nconstraints increases statistical power Vanbrabant and Rosseel\n(2020) <doi:10.4324/9780429273872-14>. Another valuable tool,\nthe Bayes factor, can evaluate evidence for multiple hypotheses\nwithout concerns about multiple testing, and can be used in\nBayesian updating Hoijtink, Mulder, van Lissa & Gu (2019)\n<doi:10.1037/met0000201>. The 'bain' R package enables\ninformative hypothesis testing using the Bayes factor. The\n'mmibain' package provides 'shiny' web applications based on\n'bain'. The RepliCrisis() function launches a 'shiny' card game\nto simulate the evaluation of replication studies while the\nmmibain() function launches a 'shiny' application to fit\nBayesian informative hypotheses evaluation models from 'bain'.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
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  "URL": "https://github.com/mightymetrika/mmibain",
  "BugReports": "https://github.com/mightymetrika/mmibain/issues",
  "Config/testthat/edition": "3",
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  "Repository": "https://mightymetrika.r-universe.dev",
  "Date/Publication": "2024-05-26 14:31:30 UTC",
  "RemoteUrl": "https://github.com/mightymetrika/mmibain",
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    "User": "root"
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  "Author": "Mackson Ncube [aut, cre],\nmightymetrika, LLC [cph, fnd]",
  "Maintainer": "Mackson Ncube <macksonncube.stats@gmail.com>",
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  "_published": "2026-05-27T09:13:41.629Z",
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  "_tags": [],
  "_topics": [
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    "bayesian",
    "hypothesis",
    "informative",
    "statistics"
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    "interpret_replication_results",
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    "process_replication_study",
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