method.RMA: Random Effects Meta-Analysis Method

In PublicationBiasBenchmark: Benchmark for Publication Bias Correction Methods

Random Effects Meta-Analysis Method

Description

Implements the publication bias-unadjusted random-effects meta-analysis.

Usage

## S3 method for class 'RMA'
method(method_name, data, settings)

Arguments

method_name	Method name (automatically passed)
data	Data frame with yi (effect sizes) and sei (standard errors)
settings	List of method settings (see Details)

Details

The following settings are implemented

"default"

Restricted Maximum Likelihood estimator (method = "REML") with Knapp-Hartung adjustment (test = "knha") for a simple random effects meta-analysis and Restricted Maximum Likelihood estimator (method = "REML") with t-distribution adjustment (test = "t") and cluster robust standard errors with small-sample adjustment (if converged, otherwise no small-sample adjustment or no cluster robust standard errors) for a multilevel random effects meta-analysis if study_ids is specified in the data

Value

Data frame with RMA results

Author(s)

František Bartoš [e-mail]

References

\insertAllCited

Examples

# Generate some example data
data <- data.frame(
  yi = c(0.2, 0.3, 0.1, 0.4, 0.25),
  sei = c(0.1, 0.15, 0.08, 0.12, 0.09)
)

# Apply RMA method
result <- run_method("RMA", data)
print(result)

PublicationBiasBenchmark documentation built on March 16, 2026, 5:07 p.m.