{
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  "Package": "PublicationBiasBenchmark",
  "Type": "Package",
  "Title": "Benchmark for Publication Bias Correction Methods",
  "Version": "0.2.1",
  "Maintainer": "František Bartoš <f.bartos96@gmail.com>",
  "Authors@R": "c(\nperson(given = \"František\",\nfamily = \"Bartoš\",\nrole = c(\"aut\", \"cre\"),\nemail   = \"f.bartos96@gmail.com\",\ncomment = c(ORCID = \"0000-0002-0018-5573\")),\nperson(given = \"Samuel\",\nfamily = \"Pawel\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0003-2779-320X\")),\nperson(given = \"Björn S.\",\nfamily = \"Siepe\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-9558-4648\")),\nperson(given = \"Petr\",\nfamily = \"Čala\",\nrole = \"aut\")\n)",
  "Description": "Implements a unified interface for benchmarking\nmeta-analytic publication bias correction methods through\nsimulation studies (see Bartoš et al., 2025,\n<doi:10.48550/arXiv.2510.19489>). It provides 1) predefined\ndata-generating mechanisms from the literature, 2) functions\nfor running meta-analytic methods on simulated data, 3)\npre-simulated datasets and pre-computed results for\nreproducible benchmarks, 4) tools for visualizing and comparing\nmethod performance.",
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  "Roxygen": "list(markdown = TRUE)",
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  "URL": "https://github.com/FBartos/PublicationBiasBenchmark,\nhttps://fbartos.github.io/PublicationBiasBenchmark/",
  "BugReports": "https://github.com/FBartos/PublicationBiasBenchmark/issues",
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  "Repository": "https://fbartos.r-universe.dev",
  "Date/Publication": "2026-05-24 10:03:57 UTC",
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  "Author": "František Bartoš [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-0018-5573>),\nSamuel Pawel [aut] (ORCID: <https://orcid.org/0000-0003-2779-320X>),\nBjörn S. Siepe [aut] (ORCID: <https://orcid.org/0000-0002-9558-4648>),\nPetr Čala [aut]",
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    "publication-bias",
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    "extra/citation.html",
    "extra/citation.json",
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    "bias_mcse",
    "compare_measures",
    "compare_single_measure",
    "compute_measures",
    "compute_single_measure",
    "coverage",
    "coverage_mcse",
    "create_empty_result",
    "dgm",
    "dgm_conditions",
    "download_dgm_datasets",
    "download_dgm_measures",
    "download_dgm_results",
    "empirical_se",
    "empirical_se_mcse",
    "empirical_variance",
    "empirical_variance_mcse",
    "get_dgm_condition",
    "get_method_extra_columns",
    "get_method_setting",
    "interval_score",
    "interval_score_mcse",
    "mean_ci_width",
    "mean_ci_width_mcse",
    "mean_generic_statistic",
    "mean_generic_statistic_mcse",
    "measure",
    "measure_mcse",
    "method",
    "method_extra_columns",
    "method_settings",
    "mse",
    "mse_mcse",
    "negative_likelihood_ratio",
    "negative_likelihood_ratio_mcse",
    "positive_likelihood_ratio",
    "positive_likelihood_ratio_mcse",
    "power",
    "power_mcse",
    "PublicationBiasBenchmark.get_option",
    "PublicationBiasBenchmark.options",
    "relative_bias",
    "relative_bias_mcse",
    "retrieve_dgm_dataset",
    "retrieve_dgm_measures",
    "retrieve_dgm_results",
    "rmse",
    "rmse_mcse",
    "run_method",
    "simulate_dgm",
    "validate_dgm_setting"
  ],
  "_help": [
    {
      "page": "compare_measures",
      "title": "Compare method with Multiple Measures for a DGM",
      "topics": [
        "compare_measures"
      ]
    },
    {
      "page": "compare_single_measure",
      "title": "Compare method with a Single Measure for a DGM",
      "topics": [
        "compare_single_measure"
      ]
    },
    {
      "page": "compute_measures",
      "title": "Compute Multiple Performance measures for a DGM",
      "topics": [
        "compute_measures"
      ]
    },
    {
      "page": "compute_single_measure",
      "title": "Compute Performance Measures",
      "topics": [
        "compute_single_measure"
      ]
    },
    {
      "page": "create_empty_result",
      "title": "Create standardized empty method result for convergence failures",
      "topics": [
        "create_empty_result"
      ]
    },
    {
      "page": "dgm",
      "title": "DGM Method",
      "topics": [
        "dgm"
      ]
    },
    {
      "page": "dgm_conditions",
      "title": "Return Pre-specified DGM Settings",
      "topics": [
        "dgm_conditions",
        "get_dgm_condition"
      ]
    },
    {
      "page": "dgm.Alinaghi2018",
      "title": "Alinaghi and Reed (2018) Data-Generating Mechanism",
      "topics": [
        "dgm.Alinaghi2018"
      ]
    },
    {
      "page": "dgm.Bom2019",
      "title": "Bom and Rachinger (2019) Data-Generating Mechanism",
      "topics": [
        "dgm.Bom2019"
      ]
    },
    {
      "page": "dgm.Carter2019",
      "title": "Carter et al. (2019) Data-Generating Mechanism",
      "topics": [
        "dgm.Carter2019"
      ]
    },
    {
      "page": "dgm.default",
      "title": "Default DGM handler",
      "topics": [
        "dgm.default"
      ]
    },
    {
      "page": "dgm.no_bias",
      "title": "Normal Unbiased Data-Generating Mechanism",
      "topics": [
        "dgm.no_bias"
      ]
    },
    {
      "page": "dgm.Stanley2017",
      "title": "Stanley, Doucouliagos, and Ioannidis (2017) Data-Generating Mechanism",
      "topics": [
        "dgm.Stanley2017"
      ]
    },
    {
      "page": "download_dgm",
      "title": "Download Datasets/Results/Measures of a DGM",
      "topics": [
        "download_dgm",
        "download_dgm_datasets",
        "download_dgm_measures",
        "download_dgm_results"
      ]
    },
    {
      "page": "measure",
      "title": "Get performance measure function",
      "topics": [
        "measure"
      ]
    },
    {
      "page": "measure_mcse",
      "title": "Get performance measure MCSE function",
      "topics": [
        "measure_mcse"
      ]
    },
    {
      "page": "measures",
      "title": "Performance Measures and Monte Carlo Standard Errors",
      "topics": [
        "bias",
        "bias_mcse",
        "coverage",
        "coverage_mcse",
        "empirical_se",
        "empirical_se_mcse",
        "empirical_variance",
        "empirical_variance_mcse",
        "interval_score",
        "interval_score_mcse",
        "mean_ci_width",
        "mean_ci_width_mcse",
        "mean_generic_statistic",
        "mean_generic_statistic_mcse",
        "measures",
        "mse",
        "mse_mcse",
        "negative_likelihood_ratio",
        "negative_likelihood_ratio_mcse",
        "positive_likelihood_ratio",
        "positive_likelihood_ratio_mcse",
        "power",
        "power_mcse",
        "relative_bias",
        "relative_bias_mcse",
        "rmse",
        "rmse_mcse"
      ]
    },
    {
      "page": "method",
      "title": "Method Method",
      "topics": [
        "method"
      ]
    },
    {
      "page": "method_extra_columns",
      "title": "Method Extra Columns",
      "topics": [
        "get_method_extra_columns",
        "method_extra_columns",
        "method_extra_columns.default"
      ]
    },
    {
      "page": "method_settings",
      "title": "Return Pre-specified Method Settings",
      "topics": [
        "get_method_setting",
        "method_settings"
      ]
    },
    {
      "page": "method.AK",
      "title": "AK Method",
      "topics": [
        "method.AK"
      ]
    },
    {
      "page": "method.default",
      "title": "Default method handler",
      "topics": [
        "method.default"
      ]
    },
    {
      "page": "method.EK",
      "title": "Endogenous Kink Method",
      "topics": [
        "method.EK"
      ]
    },
    {
      "page": "method.FMA",
      "title": "Fixed Effects Meta-Analysis Method",
      "topics": [
        "method.FMA"
      ]
    },
    {
      "page": "method.MAIVE",
      "title": "MAIVE: Meta-Analysis Instrumental Variable Estimator",
      "topics": [
        "method.MAIVE"
      ]
    },
    {
      "page": "method.mean",
      "title": "Mean Method",
      "topics": [
        "method.mean"
      ]
    },
    {
      "page": "method.pcurve",
      "title": "pcurve (P-Curve) Method",
      "topics": [
        "method.pcurve"
      ]
    },
    {
      "page": "method.PEESE",
      "title": "PEESE (Precision-Effect Estimate with Standard Errors) Method",
      "topics": [
        "method.PEESE"
      ]
    },
    {
      "page": "method.PET",
      "title": "PET (Precision-Effect Test) Method",
      "topics": [
        "method.PET"
      ]
    },
    {
      "page": "method.PETPEESE",
      "title": "PET-PEESE (Precision-Effect Test and Precision-Effect Estimate with Standard Errors) Method",
      "topics": [
        "method.PETPEESE"
      ]
    },
    {
      "page": "method.puniform",
      "title": "puniform (P-Uniform) Method",
      "topics": [
        "method.puniform"
      ]
    },
    {
      "page": "method.RMA",
      "title": "Random Effects Meta-Analysis Method",
      "topics": [
        "method.RMA"
      ]
    },
    {
      "page": "method.RoBMA",
      "title": "Robust Bayesian Meta-Analysis (RoBMA) Method",
      "topics": [
        "method.RoBMA"
      ]
    },
    {
      "page": "method.SM",
      "title": "SM (Selection Models) Method",
      "topics": [
        "method.SM"
      ]
    },
    {
      "page": "method.trimfill",
      "title": "Trim-and-Fill Meta-Analysis Method",
      "topics": [
        "method.trimfill"
      ]
    },
    {
      "page": "method.WAAPWLS",
      "title": "WAAPWLS (Weighted Average of Adequately Powered Studies) Method",
      "topics": [
        "method.WAAPWLS"
      ]
    },
    {
      "page": "method.WILS",
      "title": "Weighted and Iterated Least Squares (WILS) Method",
      "topics": [
        "method.WILS"
      ]
    },
    {
      "page": "method.WLS",
      "title": "WLS (Weighted Least Squares) Method",
      "topics": [
        "method.WLS"
      ]
    },
    {
      "page": "PublicationBiasBenchmark_options",
      "title": "Options for the PublicationBiasBenchmark package",
      "topics": [
        "PublicationBiasBenchmark.get_option",
        "PublicationBiasBenchmark.options",
        "PublicationBiasBenchmark_options"
      ]
    },
    {
      "page": "retrieve_dgm_dataset",
      "title": "Retrieve a Pre-Simulated Condition and Repetition From a DGM",
      "topics": [
        "retrieve_dgm_dataset"
      ]
    },
    {
      "page": "retrieve_dgm_measures",
      "title": "Retrieve Pre-Computed Performance measures for a DGM",
      "topics": [
        "retrieve_dgm_measures"
      ]
    },
    {
      "page": "retrieve_dgm_results",
      "title": "Retrieve a Pre-Computed Results of a Method Applied to DGM",
      "topics": [
        "retrieve_dgm_results"
      ]
    },
    {
      "page": "run_method",
      "title": "Generic method function for publication bias correction",
      "topics": [
        "run_method"
      ]
    },
    {
      "page": "simulate_dgm",
      "title": "Simulate From Data-Generating Mechanism",
      "topics": [
        "simulate_dgm"
      ]
    },
    {
      "page": "validate_dgm_setting",
      "title": "Validate DGM Settings",
      "topics": [
        "validate_dgm_setting"
      ]
    }
  ],
  "_readme": "https://github.com/fbartos/publicationbiasbenchmark/raw/HEAD/README.md",
  "_rundeps": [
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