PEESE (Precision-Effect Estimate with Standard Errors) Method

Implements the Precision-Effect Estimate with Standard Errors method for publication bias correction. PEESE regresses effect sizes against standard errors^2 to correct for publication bias. The intercept represents the bias-corrected effect size estimate. See Stanley and Doucouliagos (2014) for details.

Usage

# S3 method for class 'PEESE'
method(method_name, data, settings = NULL)

Arguments

method_name

Method name (automatically passed)

data

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

settings

List of method settings (no settings version are implemented)

Value

Data frame with PEESE results

References

Stanley TD, Doucouliagos H (2014). “Meta-regression approximations to reduce publication selection bias.” Research Synthesis Methods, 5(1), 60–78. doi:10.1002/jrsm.1095 .

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 PEESE method
result <- run_method("PEESE", data)
print(result)
#>             method   estimate standard_error   ci_lower  ci_upper   p_value BF
#> (Intercept)  PEESE 0.06720823     0.09919638 -0.1272167 0.2616331 0.5466436 NA
#>             convergence note bias_coefficient bias_p_value method_setting
#> (Intercept)        TRUE   NA         14.88532    0.1927957        default