Random Effects Meta-Analysis Method

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)

Value

Data frame with RMA results

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

References

There are no references for Rd macro \insertAllCites on this help page.

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)
#>   method  estimate standard_error   ci_lower  ci_upper    p_value BF
#> 1    RMA 0.2255651     0.05033069 0.08582468 0.3653055 0.01097584 NA
#>   convergence note tau_estimate tau_ci_lower tau_ci_upper tau_p_value
#> 1        TRUE   NA   0.05721499            0    0.3038259   0.2941821
#>   method_setting
#> 1        default