dgm.no_bias: Normal Unbiased Data-Generating Mechanism

In PublicationBiasBenchmark: Benchmark for Publication Bias Correction Methods

Normal Unbiased Data-Generating Mechanism

Description

An example data-generating mechanism to simulate effect sizes without publication bias.

Usage

## S3 method for class 'no_bias'
dgm(dgm_name, settings)

Arguments

dgm_name	DGM name (automatically passed)
settings	List containing mean_effect Mean effect heterogeneity Effect heterogeneity n_studies Number of effect size estimates

Details

Sample sizes of individual effect size estimates are generated from a negative binomial distribution based on empirical sample size distribution presented in Appendix B of \insertCitemaier2023robust;textualPublicationBiasBenchmark

Value

Data frame with

yi

effect size

sei

standard error

ni

sample size

es_type

effect size type

Author(s)

František Bartoš [e-mail]

References

\insertAllCited

See Also

dgm(), validate_dgm_setting()

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