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  "Title": "Simulation-Based Power Analysis for Factorial Designs",
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  "Authors@R": "c(person(given = \"Aaron\",\nfamily = \"Caldwell\",\nrole = c(\"aut\", \"cre\"),\nemail = \"arcaldwell49@gmail.com\"),\nperson(given = \"Daniel\",family = \"Lakens\",\nrole = c(\"aut\"),\nemail = \"D.Lakens@tue.nl\"),\nperson(given = \"Lisa\",\nfamily = \"DeBruine\",\nrole = c(\"ctb\"),\nemail = \"debruine@gmail.com\"),\nperson(given = \"Jonathon\",\nfamily = \"Love\",\nrole = c(\"ctb\"),\nemail = \"jon@thon.cc\"),\nperson(given = \"Frederik\",\nfamily = \"Aust\",\nemail = \"frederik.aust@uni-koeln.de\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0003-4900-788X\")))",
  "Description": "Functions to perform simulations of ANOVA designs of up to\nthree factors. Calculates the observed power and average\nobserved effect size for all main effects and interactions in\nthe ANOVA, and all simple comparisons between conditions.\nIncludes functions for analytic power calculations and\nadditional helper functions that compute effect sizes for ANOVA\ndesigns, observed error rates in the simulations, and functions\nto plot power curves. Please see Lakens, D., & Caldwell, A. R.\n(2021). \"Simulation-Based Power Analysis for Factorial Analysis\nof Variance Designs\". <doi:10.1177/2515245920951503>.",
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    "power_oneway_between",
    "power_oneway_within",
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    "power_threeway_between",
    "power_twoway_between",
    "power.ftest",
    "Superpower_options"
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    {
      "page": "alpha_standardized",
      "title": "Compute standardized alpha level based on unstandardized alpha level and the number of observations N.",
      "topics": [
        "alpha_standardized"
      ]
    },
    {
      "page": "ANCOVA_analytic",
      "title": "Power Calculations for Factorial ANCOVAs",
      "topics": [
        "ANCOVA_analytic"
      ]
    },
    {
      "page": "ANCOVA_contrast",
      "title": "Power Calculations for ANCOVA Contrasts",
      "topics": [
        "ANCOVA_contrast"
      ]
    },
    {
      "page": "ancova_power-methods",
      "title": "Methods for ancova_power objects",
      "topics": [
        "ancova_power-methods",
        "plot.ancova_power",
        "print.ancova_power"
      ]
    },
    {
      "page": "ANOVA_compromise",
      "title": "Justify your alpha level by minimizing or balancing Type 1 and Type 2 error rates for ANOVAs.",
      "topics": [
        "ANOVA_compromise"
      ]
    },
    {
      "page": "ANOVA_design",
      "title": "Design function used to specify the parameters to be used in simulations",
      "topics": [
        "ANOVA_design"
      ]
    },
    {
      "page": "ANOVA_exact",
      "title": "Simulates an exact dataset (mu, sd, and r represent empirical, not population, mean and covariance matrix) from the design to calculate power",
      "topics": [
        "ANOVA_exact",
        "ANOVA_exact2"
      ]
    },
    {
      "page": "ANOVA_power",
      "title": "Simulation function used to estimate power",
      "topics": [
        "ANOVA_power"
      ]
    },
    {
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      "title": "Methods for design_aov objects",
      "topics": [
        "design_aov-methods",
        "plot.design_aov",
        "print.design_aov"
      ]
    },
    {
      "page": "emmeans_power",
      "title": "Compute power for 'emmeans' contrasts",
      "topics": [
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        "emmeans_power.data.frame",
        "emmeans_power.emmGrid",
        "emmeans_power.summary_em"
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    },
    {
      "page": "morey_plot",
      "title": "Plot out power sensitivity plots for t or F tests",
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        "morey_plot.ftest",
        "morey_plot.ttest"
      ]
    },
    {
      "page": "mu_from_ES",
      "title": "Convenience function to calculate the means for between designs with one factor (One-Way ANOVA). Can be used to determine the means that should yield a specified effect sizes (expressed in Cohen's f).",
      "topics": [
        "mu_from_ES"
      ]
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      "title": "Methods for opt_alpha objects",
      "topics": [
        "opt_alpha-methods",
        "plot.opt_alpha",
        "print.opt_alpha"
      ]
    },
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      "page": "optimal_alpha",
      "title": "Justify your alpha level by minimizing or balancing Type 1 and Type 2 error rates.",
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    },
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      "title": "Compute standardized alpha level based on unstandardized alpha level and the number of observations N.",
      "topics": [
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      ]
    },
    {
      "page": "plot_power",
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      "topics": [
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      "topics": [
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      "title": "Analytic power calculation for three-way between designs.",
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    },
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      "title": "Analytic power calculation for two-way between designs.",
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        "plot.sim_result",
        "print.sim_result",
        "sim_result-methods"
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