WLS (Weighted Least Squares) Method

Implements the Weighted Least Squares method for meta-analysis. WLS fits a weighted regression model with effect sizes as the outcome and weights based on the inverse of the squared standard errors. The intercept represents the weighted average effect size estimate.

Usage

# S3 method for class 'WLS'
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 WLS results

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 WLS method
result <- run_method("WLS", data)
print(result)
#>             method  estimate standard_error  ci_lower  ci_upper    p_value BF
#> (Intercept)    WLS 0.2179928     0.04998789 0.1200165 0.3159691 0.01205352 NA
#>             convergence note method_setting
#> (Intercept)        TRUE   NA        default