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  "Package": "hmetad",
  "Title": "Fit the Meta-D' Model of Confidence Ratings Using 'brms'",
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  "Authors@R": "c(\nperson(\"Kevin\", \"O'Neill\", email=\"kevin.o'neill@ucl.ac.uk\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-7401-9802\")),\nperson(\"Stephen\", \"Fleming\", email=\"stephen.fleming@ucl.ac.uk\", role = c(\"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0003-0233-4891\"))\n)",
  "Description": "Implementation of Bayesian regressions over the meta-d'\nmodel of psychological data from two alternative forced choice\ntasks with ordinal confidence ratings. For more information,\nsee Maniscalco & Lau (2012) <doi:10.1016/j.concog.2011.09.021>.\nThe package is a front-end to the 'brms' package, which\nfacilitates a wide range of regression designs, as well as\ntools for efficiently extracting posterior estimates, plotting,\nand significance testing.",
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  "URL": "https://metacoglab.github.io/hmetad/,\nhttps://github.com/metacoglab/hmetad",
  "BugReports": "https://github.com/metacoglab/hmetad/issues",
  "Config/pak/sysreqs": "make libicu-dev",
  "Repository": "https://metacoglab.r-universe.dev",
  "Date/Publication": "2026-05-15 15:26:05 UTC",
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  "Author": "Kevin O'Neill [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0001-7401-9802>),\nStephen Fleming [aut, cph] (ORCID:\n<https://orcid.org/0000-0003-0233-4891>)",
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    "add_epred_draws_metad",
    "add_epred_rvars_metad",
    "add_linpred_draws_metad",
    "add_linpred_rvars_metad",
    "add_mean_confidence_draws",
    "add_mean_confidence_rvars",
    "add_metacognitive_bias_draws",
    "add_metacognitive_bias_rvars",
    "add_predicted_draws_metad",
    "add_predicted_rvars_metad",
    "add_roc1_draws",
    "add_roc1_rvars",
    "add_roc2_draws",
    "add_roc2_rvars",
    "aggregate_metad",
    "cor_matrix",
    "cov_matrix",
    "epred_draws_metad",
    "epred_rvars_metad",
    "example_data",
    "example_model",
    "fit_metad",
    "joint_response",
    "linpred_draws_metad",
    "linpred_rvars_metad",
    "mean_confidence_draws",
    "mean_confidence_rvars",
    "metac2_parameters",
    "metacognitive_bias_draws",
    "metacognitive_bias_rvars",
    "metad",
    "metad_pmf",
    "normal_lccdf",
    "normal_lcdf",
    "predicted_draws_metad",
    "predicted_rvars_metad",
    "response_probabilities",
    "rmatrixnorm",
    "roc1_draws",
    "roc1_rvars",
    "roc2_draws",
    "roc2_rvars",
    "sim_metad",
    "sim_metad_condition",
    "sim_metad_participant",
    "sim_metad_participant_condition",
    "stanvars_metad",
    "to_signed",
    "to_unsigned",
    "type1_response",
    "type2_response"
  ],
  "_help": [
    {
      "page": "aggregate_metad",
      "title": "Aggregate 'data' by 'response', 'confidence', and other columns",
      "topics": [
        "aggregate_metad"
      ]
    },
    {
      "page": "cor_matrix",
      "title": "Generate a correlation matrix with all off-diagonal values equal to 'r'",
      "topics": [
        "cor_matrix"
      ]
    },
    {
      "page": "cov_matrix",
      "title": "Generate a covariance matrix.",
      "topics": [
        "cov_matrix"
      ]
    },
    {
      "page": "epred_draws_metad",
      "title": "Obtain posterior draws of joint response probabilities",
      "topics": [
        "add_epred_draws_metad",
        "add_epred_rvars_metad",
        "epred_draws_metad",
        "epred_rvars_metad"
      ]
    },
    {
      "page": "example_data",
      "title": "Simulated data for example model fitting",
      "topics": [
        "example_data"
      ]
    },
    {
      "page": "example_model",
      "title": "Example meta-d' model for model post-processing",
      "topics": [
        "example_model"
      ]
    },
    {
      "page": "fit_metad",
      "title": "Fit the meta-d' model using 'brms' package",
      "topics": [
        "fit_metad"
      ]
    },
    {
      "page": "responses",
      "title": "Convert between separate and joint type 1/type 2 responses",
      "topics": [
        "joint_response",
        "type1_response",
        "type2_response"
      ]
    },
    {
      "page": "linpred_draws_metad",
      "title": "Obtain posterior draws of meta-d' model parameters",
      "topics": [
        "add_linpred_draws_metad",
        "add_linpred_rvars_metad",
        "linpred_draws_metad",
        "linpred_rvars_metad"
      ]
    },
    {
      "page": "mean_conf_draws",
      "title": "Obtain posterior draws of mean confidence",
      "topics": [
        "add_mean_confidence_draws",
        "add_mean_confidence_rvars",
        "mean_confidence_draws",
        "mean_confidence_rvars"
      ]
    },
    {
      "page": "metac2_parameters",
      "title": "Obtain a vector of the names of the 'K-1' parameters representing the differences between successive confidence criteria for the meta-d' model with 'K' levels of confidence.",
      "topics": [
        "metac2_parameters"
      ]
    },
    {
      "page": "bias_draws",
      "title": "Obtain posterior draws of an index of metacognitive bias",
      "topics": [
        "add_metacognitive_bias_draws",
        "add_metacognitive_bias_rvars",
        "metacognitive_bias_draws",
        "metacognitive_bias_rvars"
      ]
    },
    {
      "page": "metad",
      "title": "'brms' family for the metad' model",
      "topics": [
        "metad"
      ]
    },
    {
      "page": "metad_pmf",
      "title": "Generate (log) probability simplex over the joint type 1/type 2 responses",
      "topics": [
        "metad_pmf"
      ]
    },
    {
      "page": "normal_dist",
      "title": "Normal cumulative distribution functions",
      "topics": [
        "normal_lccdf",
        "normal_lcdf"
      ]
    },
    {
      "page": "predicted_draws_metad",
      "title": "Obtain posterior predictions of joint responses",
      "topics": [
        "add_predicted_draws_metad",
        "add_predicted_rvars_metad",
        "predicted_draws_metad",
        "predicted_rvars_metad"
      ]
    },
    {
      "page": "response_probabilities",
      "title": "Compute joint response probabilities from aggregated counts",
      "topics": [
        "response_probabilities"
      ]
    },
    {
      "page": "rmatrixnorm",
      "title": "Sample from a matrix-normal distribution",
      "topics": [
        "rmatrixnorm"
      ]
    },
    {
      "page": "roc1_draws",
      "title": "Obtain posterior draws of the pseudo type 1 receiver operating characteristic (ROC) curve.",
      "topics": [
        "add_roc1_draws",
        "add_roc1_rvars",
        "roc1_draws",
        "roc1_rvars"
      ]
    },
    {
      "page": "roc2_draws",
      "title": "Obtain posterior draws of the response-specific type 2 receiver operating characteristic (ROC) curves.",
      "topics": [
        "add_roc2_draws",
        "add_roc2_rvars",
        "roc2_draws",
        "roc2_rvars"
      ]
    },
    {
      "page": "sim_metad",
      "title": "Simulate from the meta-d' model",
      "topics": [
        "sim_metad"
      ]
    },
    {
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      "title": "Simulate from the meta-d' model across separate conditions",
      "topics": [
        "sim_metad_condition"
      ]
    },
    {
      "page": "sim_metad_participant",
      "title": "Simulate from the hierarchical meta-d' model",
      "topics": [
        "sim_metad_participant"
      ]
    },
    {
      "page": "sim_metad_participant_condition",
      "title": "Simulate from the hierarchical meta-d' model across within-participant conditions",
      "topics": [
        "sim_metad_participant_condition"
      ]
    },
    {
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      "title": "Generate Stan code for the meta-d' model",
      "topics": [
        "stanvars_metad"
      ]
    },
    {
      "page": "signed",
      "title": "Convert binary variable x between \\{0, 1\\} and \\{-1, 1\\}",
      "topics": [
        "to_signed",
        "to_unsigned"
      ]
    }
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