{
  "_id": "6aafcdaa3d719c1f8408251e",
  "Package": "ssutil",
  "Title": "Sample Size Calculation Tools",
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  "Authors@R": "c(\nperson(\ngiven = \"John J.\",\nfamily = \"Aponte\",\nrole = c(\"aut\", \"cre\"),\nemail = \"john.j.aponte@gmail.com\",\ncomment = c(ORCID = \"0000-0002-3014-3673\")),\nperson(\ngiven = \"Chris\",\nfamily = \"Gast\",\nemail = \"cgast@path.org\",\nrole = \"ctb\")\n)",
  "Description": "Functions for sample size estimation and simulation in\nclinical trials. Includes methods for selecting the best group\nusing the Indifference-zone approach, as well as designs for\nnon-inferiority, equivalence, and negative binomial models. For\nthe sample size calculation for non-inferiority of vaccines,\nthe approach is based on Fleming, Powers, and Huang (2021)\n<doi:10.1177/1740774520988244>. The Indifference-zone approach\nis based on Sobel and Huyett (1957)\n<doi:10.1002/j.1538-7305.1957.tb02411.x> and Bechhofer,\nSantner, and Goldsman (1995, ISBN:978-0-471-57427-9).",
  "License": "AGPL (>= 3)",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "Language": "en-US",
  "Config/testthat/edition": "3",
  "VignetteBuilder": "knitr",
  "URL": "https://johnaponte.github.io/ssutil/,\nhttps://github.com/johnaponte/ssutil",
  "BugReports": "https://github.com/johnaponte/ssutil/issues",
  "Config/roxygen2/version": "8.1.0",
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  "Date/Publication": "2026-09-17 15:42:25 UTC",
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  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
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    "Date": "2026-09-20 12:09:04 UTC",
    "User": "root"
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  "Author": "John J. Aponte [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-3014-3673>),\nChris Gast [ctb]",
  "Maintainer": "John J. Aponte <john.j.aponte@gmail.com>",
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  "_created": "2026-09-20T12:09:04.000Z",
  "_published": "2026-09-20T12:12:26.161Z",
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    "sim_power_best_bin_rank",
    "sim_power_best_binomial",
    "sim_power_best_norm_rank",
    "sim_power_best_normal",
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    "ss_best_normal",
    "ss_ni_ve",
    "wcs_power_best_binomial"
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      "title": "Create an Empirical Power Result object",
      "topics": [
        "empirical_power_result"
      ]
    },
    {
      "page": "format.power_events_rate",
      "title": "Format method for power_events_rate class",
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        "format.power_events_rate"
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    },
    {
      "page": "format.power_single_rate",
      "title": "Format method for power_single_rate class",
      "topics": [
        "format.power_single_rate"
      ]
    },
    {
      "page": "is.empirical_power_result",
      "title": "Check if an object is a sim_power_result",
      "topics": [
        "is.empirical_power_result"
      ]
    },
    {
      "page": "multp",
      "title": "Multivariate Normal Equicoordinate Cumulative Distribution Function",
      "topics": [
        "multp"
      ]
    },
    {
      "page": "multz",
      "title": "Calculate the Upper Equicoordinate Point of a Multivariate Normal Distribution",
      "topics": [
        "multz"
      ]
    },
    {
      "page": "power_best_binomial",
      "title": "Power to Correctly Select the Best Group in a Binomial Test",
      "topics": [
        "power_best_binomial"
      ]
    },
    {
      "page": "power_best_normal",
      "title": "Power calculation for the Indifferent-zone approach for normal outcomes",
      "topics": [
        "power_best_normal"
      ]
    },
    {
      "page": "power_events_rate",
      "title": "Probability of Observing At Least a Given Number of Events",
      "topics": [
        "power_events_rate"
      ]
    },
    {
      "page": "power_single_rate",
      "title": "Detectable Event Rate with Specified Power and Sample Size",
      "topics": [
        "power_single_rate"
      ]
    },
    {
      "page": "print.empirical_power_result",
      "title": "Print method for empirical_power_result",
      "topics": [
        "print.empirical_power_result"
      ]
    },
    {
      "page": "print.power_events_rate",
      "title": "Print method for class power_events_rate",
      "topics": [
        "print.power_events_rate"
      ]
    },
    {
      "page": "print.power_single_rate",
      "title": "Print method for class power_single_rate",
      "topics": [
        "print.power_single_rate"
      ]
    },
    {
      "page": "prophr",
      "title": "Calculate Event Probability in the Experimental Group Given a Hazard Ratio",
      "topics": [
        "prophr"
      ]
    },
    {
      "page": "sim_power_best_bin_rank",
      "title": "Simulate Power to Rank the Best Group Using Binomial Outcomes",
      "topics": [
        "sim_power_best_bin_rank"
      ]
    },
    {
      "page": "sim_power_best_binomial",
      "title": "Simulate Power to Select the Best Group Using Binomial Outcomes",
      "topics": [
        "sim_power_best_binomial"
      ]
    },
    {
      "page": "sim_power_best_norm_rank",
      "title": "Simulate Power to Select Best Group by Ranks (Normal Outcomes)",
      "topics": [
        "sim_power_best_norm_rank"
      ]
    },
    {
      "page": "sim_power_best_normal",
      "title": "Simulate Power to Select Best Group (Normal Outcomes)",
      "topics": [
        "sim_power_best_normal"
      ]
    },
    {
      "page": "sim_power_equivalence_normal",
      "title": "Empirical Power for Equivalence (Normal Outcomes)",
      "topics": [
        "sim_power_equivalence_normal"
      ]
    },
    {
      "page": "sim_power_nbinom",
      "title": "Empirical Power for Negative Binomial Comparison",
      "topics": [
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    },
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      "title": "Empirical Power for Non-Inferiority (Normal Outcomes)",
      "topics": [
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    },
    {
      "page": "ss_best_binomial",
      "title": "Sample Size to Select the Best Group in a Binomial Test",
      "topics": [
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    },
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      "title": "Sample Size and Non-Inferiority Margin for Vaccine Efficacy Trials",
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      "title": "Tidy Method for empirical_power_result",
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      "title": "Worst‐Case Scenario Power for the Best Binomial Group",
      "topics": [
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