method.pcurve: pcurve (P-Curve) Method

In PublicationBiasBenchmark: Benchmark for Publication Bias Correction Methods

pcurve (P-Curve) Method

Description

Implements the p-Curve method which analyzes the distribution of p-values from significant studies to assess whether the significant findings reflect true effects or QRP/publication bias. The method also provides tests for the evidential value, lack of evidential value, and p-hacking. See \insertCitesimonsohn2014pcurve;textualPublicationBiasBenchmark for details.

The current implementation does not provide a test against the null hypothsis of no effect and does not produce confidence intervals of the estimate.

Usage

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

Arguments

method_name	Method name (automatically passed)
data	Data frame with yi (effect sizes), sei (standard errors), and ni (sample sizes wherever available, otherwise set to Inf)
settings	List of method settings (see Details)

Details

The following settings are implemented

"default"

no options

Value

Data frame with P-Curve 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 pcurve method
result <- run_method("pcurve", data)
print(result)

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