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This function provides pairwise comparison of method for Data-Generating Mechanisms (DGMs). It compares method performance on a condition-by-condition basis using estimates. For each pair of method, if method A has an estimate closer to the true value than method B, it gets a score of 1, if further it gets 0, and if equal it gets 0.5.

Usage

compare_single_measure(
  dgm_name,
  measure_name,
  method,
  method_setting,
  conditions,
  estimate_col = "estimate",
  true_effect_col = "mean_effect",
  convergence_col = "convergence",
  method_replacements = NULL,
  n_repetitions = 1000,
  overwrite = FALSE,
  path = NULL,
  ...
)

Arguments

dgm_name

Character string specifying the name of the DGM dataset to download.

measure_name

Name of the measure to compute (e.g., "bias", "mse")

method

Character vector of method names

method_setting

Character vector of method settings, must be same length as method

conditions

Data frame of conditions from dgm_conditions()

estimate_col

Character string specifying the column name containing parameter estimates. Default is "estimate"

true_effect_col

Character string specifying the column name in conditions data frame containing true effect sizes. Default is "mean_effect"

convergence_col

Character string specifying the column name containing convergence indicators. Default is "convergence"

method_replacements

Named list of replacement method specifications. Each element should be named with the "method-method_setting" combination (e.g., "RMA-default") and contain a named list with:

  • method: Character vector of replacement method names

  • method_setting: Character vector of replacement method settings (same length as methods)

  • power_test_type: Optional character vector of power test types for each replacement method (same length as methods). If not specified, uses the main power_test_type parameter

If multiple elements are specified within the vectors, these replacements are applied consecutively in case the previous replacements also failed to converge. Defaults to NULL, i.e., omitting repetitions without converged results on method-by-method basis.

n_repetitions

Number of repetitions in each condition. Necessary method replacement. Defaults to 1000.

overwrite

Logical indicating whether to overwrite existing files. Defaults to FALSE, which means only missing files will be downloaded.

path

Character string specifying the directory path where the datasets/results/measures should be saved. Defaults to the location specified via PublicationBiasBenchmark.get_option("simulation_directory"). The objects are stored in dgm_name/datasets, dgm_name/results, dgm_name/measures subfolders.

...

Additional arguments passed to measure functions

Value

Data frame with pairwise comparison scores in long format (method_a, method_b, score)