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  "Package": "InteractionPoweR",
  "Title": "Power Analyses for Interaction Effects in Cross-Sectional\nRegressions",
  "Version": "0.2.4",
  "Authors@R": "c(person(given = \"David\",\nfamily = \"Baranger\",\nrole = c(\"aut\", \"cre\"),\nemail = \"dbaranger@gmail.com\" ),\nperson(given = \"Andrew\",\nfamily = \"Castillo\",\nrole = c(\"aut\"),\nemail = \"casti179@purdue.edu\"),\nperson(given = \"Brandon\",\nfamily = \"Goldstein\",\nrole = \"ctb\",\nemail = \"brandonlgoldstein@gmail.com\")   ,\nperson(given = \"Megan\",\nfamily = \"Finsaas\",\nrole = \"ctb\",\nemail = \"megan.finsaas@gmail.com\")  ,\nperson(given = \"Thomas\",\nfamily = \"Olino\",\nrole = \"ctb\",\nemail = \"thomas.olino@gmail.com\")  ,\nperson(given = \"Colin\",\nfamily = \"Vize\",\nrole = \"ctb\",\nemail = \"vizece@upmc.edu\")  ,\nperson(given = \"Don\",\nfamily = \"Lynam\",\nrole = \"ctb\",\nemail = \"dlynam@purdue.edu\")\n)",
  "Description": "Power analysis for regression models which test the\ninteraction of two or three independent variables on a single\ndependent variable. Includes options for correlated interacting\nvariables and specifying variable reliability. Two-way\ninteractions can include continuous, binary, or ordinal\nvariables. Power analyses can be done either analytically or\nvia simulation.  Includes tools for simulating single data sets\nand visualizing power analysis results. The primary functions\nare power_interaction_r2() and power_interaction() for two-way\ninteractions, and power_interaction_3way_r2() for three-way\ninteractions. The function run_pos_power_search() provides a\nstability analysis for two-way interactions. Please cite as:\nBaranger DAA, Finsaas MC, Goldstein BL, Vize CE, Lynam DR,\nOlino TM (2023). \"Tutorial: Power analyses for interaction\neffects in cross-sectional regressions.\"\n<doi:10.1177/25152459231187531>. If you use the stability\nanalyses, please cite: Castillo A, Miller JD, Vize C, Baranger\nDAA, Lynam DR. \"When Do Interaction/Moderation Effects\nStabilize in Linear\nRegression?\"<doi:10.1177/25152459251407860>.",
  "Maintainer": "David Baranger <dbaranger@gmail.com>",
  "URL": "https://dbaranger.github.io/InteractionPoweR/,\nhttps://doi.org/10.1177/25152459231187531,\nhttps://doi.org/10.1177/25152459251407860",
  "BugReports": "https://github.com/dbaranger/InteractionPoweR/issues",
  "License": "GPL (>= 3)",
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  "Repository": "https://dbaranger.r-universe.dev",
  "Date/Publication": "2026-03-23 20:21:14 UTC",
  "RemoteUrl": "https://github.com/dbaranger/interactionpower",
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  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
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  "Author": "David Baranger [aut, cre],\nAndrew Castillo [aut],\nBrandon Goldstein [ctb],\nMegan Finsaas [ctb],\nThomas Olino [ctb],\nColin Vize [ctb],\nDon Lynam [ctb]",
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      "title": "compute_adjustment",
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      "title": "See the correlation matrix for a 3-way interaction",
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      "title": "Generate interaction data set",
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      "title": "Plot power curve",
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