{
  "_id": "6a107658acfb0bcc41cacb4a",
  "Package": "Spower",
  "Title": "Power Analyses using Monte Carlo Simulations",
  "Version": "0.6.3",
  "Authors@R": "person(\"Phil\", family=\"Chalmers\", email =\n\"rphilip.chalmers@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID=\"0000-0001-5332-2810\"))",
  "Description": "Provides a general purpose simulation-based power analysis\nAPI for routine and customized simulation experimental designs.\nThe package focuses exclusively on Monte Carlo simulation\nexperiment variants of (expected) prospective power analyses,\ncriterion analyses, compromise analyses, sensitivity analyses,\nand a priori/post-hoc analyses. The default simulation\nexperiment functions defined within the package provide\nstochastic variants of the power analysis subroutines in\nG*Power 3.1 (Faul, Erdfelder, Buchner, and Lang, 2009)\n<doi:10.3758/brm.41.4.1149>, along with various other\nparametric and non-parametric power analysis applications\n(e.g., mediation analyses) and support for Bayesian power\nanalysis by way of Bayes factors or posterior probability\nevaluations. Additional functions for building empirical power\ncurves, reanalyzing simulation information, and for increasing\nthe precision of the resulting power estimates are also\nincluded, each of which utilize similar API structures. For\nfurther details see the associated publication in Chalmers\n(2025) <doi:10.3758/s13428-025-02787-z>.",
  "VignetteBuilder": "knitr",
  "ByteCompile": "yes",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "Maintainer": "Phil Chalmers <rphilip.chalmers@gmail.com>",
  "URL": "https://philchalmers.github.io/Spower/,\nhttps://github.com/philchalmers/Spower",
  "BugReports": "https://github.com/philchalmers/Spower/issues?state=open",
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  "Repository": "https://philchalmers.r-universe.dev",
  "Date/Publication": "2026-05-06 13:08:34 UTC",
  "RemoteUrl": "https://github.com/philchalmers/spower",
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    "User": "root"
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  "Author": "Phil Chalmers [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-5332-2810>)",
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  "_published": "2026-05-22T15:29:28.761Z",
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    "p_chisq.test",
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    "p_mauchly.test",
    "p_mcnemar.test",
    "p_mediation",
    "p_prop.test",
    "p_r",
    "p_r.cat",
    "p_scale",
    "p_shapiro.test",
    "p_slr",
    "p_t.test",
    "p_var.test",
    "p_wilcox.test",
    "Spower",
    "SpowerBatch",
    "SpowerCurve"
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      "title": "Get previously evaluated Spower execution",
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      "title": "Evaluate whether a confidence interval is within a tolerable interval",
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    {
      "page": "is.outside_CI",
      "title": "Evaluate whether parameter is outside a given confidence interval",
      "topics": [
        "is.outside_CI"
      ]
    },
    {
      "page": "p_2r",
      "title": "p-value from comparing two or more correlations simulation",
      "topics": [
        "gen_2r",
        "p_2r"
      ]
    },
    {
      "page": "p_anova.test",
      "title": "p-value from one-way ANOVA simulation",
      "topics": [
        "gen_anova.test",
        "p_anova.test"
      ]
    },
    {
      "page": "p_chisq.test",
      "title": "p-value from chi-squared test simulation",
      "topics": [
        "gen_chisq.test",
        "p_chisq.test"
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    },
    {
      "page": "p_glm",
      "title": "p-value from (generalized) linear regression model simulations with fixed predictors",
      "topics": [
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        "p_glm"
      ]
    },
    {
      "page": "p_kruskal.test",
      "title": "p-value from Kruskal-Wallis Rank Sum Test simulation",
      "topics": [
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        "p_kruskal.test"
      ]
    },
    {
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      "title": "p-value from Kolmogorov-Smirnov one- or two-sample simulation",
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      "title": "p-value from global linear regression model simulation",
      "topics": [
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      "title": "p-value from Mauchly's Test of Sphericity simulation",
      "topics": [
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        "mauchlys.test",
        "p_mauchly.test"
      ]
    },
    {
      "page": "p_mcnemar.test",
      "title": "p-value from McNemar test simulation",
      "topics": [
        "gen_mcnemar.test",
        "p_mcnemar.test"
      ]
    },
    {
      "page": "p_mediation",
      "title": "p-value from three-variable mediation analysis simulation",
      "topics": [
        "gen_mediation",
        "p_mediation"
      ]
    },
    {
      "page": "p_prop.test",
      "title": "p-value from proportion test simulation",
      "topics": [
        "gen_prop.test",
        "p_prop.test"
      ]
    },
    {
      "page": "p_r",
      "title": "p-value from correlation simulation",
      "topics": [
        "gen_r",
        "p_r"
      ]
    },
    {
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      "title": "p-value from tetrachoric/polychoric or polyserial",
      "topics": [
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    },
    {
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      "title": "p-value from Scale Test simulation",
      "topics": [
        "p_scale"
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    },
    {
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    {
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        "p_slr"
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      "title": "p-value from independent/paired samples t-test simulation",
      "topics": [
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        "p_t.test"
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    },
    {
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      "title": "p-value from variance test simulation",
      "topics": [
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        "p_var.test"
      ]
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      "title": "p-value from Wilcoxon (signed rank) test simulation",
      "topics": [
        "p_wilcox.test"
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    },
    {
      "page": "Spower",
      "title": "Simulation-based Power Analyses",
      "topics": [
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        "as.data.frame.SpowerBatch",
        "interval",
        "print.Spower",
        "print.SpowerBatch",
        "Spower",
        "SpowerBatch",
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      "title": "Update compromise or prospective/post-hoc power analysis without re-simulating",
      "topics": [
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  "_vignettes": [
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      "source": "gpower_examples.Rmd",
      "filename": "gpower_examples.html",
      "title": "G*Power examples evaluated with Spower",
      "author": "Phil Chalmers",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Correlation",
        "Example 3.3; Difference from constant (one sample case)",
        "Test against constant $\\rho_0=0$",
        "Example 27.3; Correlation - inequality of two independent Pearson r's",
        "Example 28.3.1; Correlation - inequality of two dependent Pearson r's (no common index)",
        "Example 28.3.2; Correlation - inequality of two dependent Pearson r's (common index)",
        "Example 28.3.3; sensitivity analysis",
        "Example 16.3; Point-biserial correlation",
        "Example 31.3; tetrachoric correlation",
        "Proportions",
        "Example 4.3; One sample proportion tests",
        "Example 22.1; Wilcoxon signed-rank test",
        "Laplace($\\mu$, 1) version",
        "Example 5.3; Two dependent proportions test (McNemar's test)",
        "Multiple Linear Regression (Fixed IVs)",
        "Example 13.1",
        "Example 14.3",
        "Example 14.3b",
        "Multiple Linear Regression (Random IVs)",
        "Example 7.3",
        "Simple linear regression",
        "Example 12.3",
        "Fixed effects ANOVA - One way (F-test)",
        "Example 10.3",
        "$t$-test: Linear regression (two groups)",
        "Example 17.3 and 18.3",
        "Variance tests",
        "Example 26.3; Difference from constant (one sample case)",
        "Example 15.3; Two-sample variance test",
        "t-tests",
        "Example 19.3; Paired samples t-test",
        "Example 20.3; One-sample t-test",
        "Wilcoxon tests",
        "Example 22.3; One-sample test with normal distribution",
        "Two-sample test with Laplace distributions",
        "Example 23.3: Paired-samples test with Laplace distributions"
      ],
      "created": "2024-10-24 14:21:40",
      "modified": "2026-05-06 13:08:34",
      "commits": 69
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      "filename": "SpowerIntro.html",
      "title": "Introduction to the Spower package",
      "author": "Phil Chalmers",
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