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This function provides a unified interface to various publication bias correction methods. The specific method is determined by the first argument. See vignette("Adding_New_Methods", package = "PublicationBiasBenchmark") for details of extending the package with new methods

Usage

run_method(method_name, data, settings = NULL, silent = FALSE)

Arguments

method_name

Character string specifying the method type

data

Data frame containing yi (effect sizes) and sei (standard errors)

settings

Either a character identifying a method version or list containing method-specific settings. An emty input will result in running the default (first implemented) version of the method.

silent

Logical indicating whether error messages from the method should be suppressed.

Value

A data frame with standardized method results

Output Structure

The returned data frame follows a standardized schema that downstream functions rely on. All methods return the following columns:

  • method (character): The name of the method used.

  • estimate (numeric): The meta-analytic effect size estimate.

  • standard_error (numeric): Standard error of the estimate.

  • ci_lower (numeric): Lower bound of the 95% confidence interval.

  • ci_upper (numeric): Upper bound of the 95% confidence interval.

  • p_value (numeric): P-value for the estimate.

  • BF (numeric): Bayes Factor for the estimate.

  • convergence (logical): Whether the method converged successfully.

  • note (character): Additional notes describing convergence issues.

Some methods may include additional method-specific columns beyond these standard columns. Use get_method_extra_columns() to query which additional columns a particular method returns.

Examples

# Example usage with PET method
data <- data.frame(
  yi = c(0.2, 0.3, 0.1, 0.4),
  sei = c(0.1, 0.15, 0.08, 0.12)
)
result <- run_method("RMA", data, "default")

# Example usage with PETPEESE method
# result <- method("PETPEESE", data)