A tutorial for calculating field-specific effect size distributions.

Area of Science:

• Statistics
• Research Methodology

Background:

• Effect sizes are crucial for interpreting study results and planning future research.
• Misinterpretation of effect sizes is common, often stemming from over-reliance on non-specific benchmarks.
• Inaccurate interpretations can lead to flawed conclusions and inflated false-positive rates.

Purpose of the Study:

• Introduce the ESDist R package for calculating empirically derived effect size benchmarks.
• Provide researchers with a tool to accurately plan new studies and interpret existing findings.
• Address limitations in current effect size benchmark usage.

Main Methods:

• The ESDist R package computes effect size distributions (ESDs) from meta-analytic data.
• It allows for the calculation of empirically derived benchmarks and detectable effect sizes.
• Features include a priori power analysis integration and bias-corrected, variance-weighted benchmarks.

Main Results:

• ESDist facilitates the extraction of data from existing meta-analyses.
• The package enables the creation of field-specific or research-question-specific effect size benchmarks.
• It offers a more accurate approach to sample size estimation and result interpretation.

Conclusions:

• The ESDist R package offers a robust solution to the problem of effect size misinterpretation.
• It empowers researchers to conduct more accurate power analyses and contextualize their findings.
• This tool enhances the reliability and validity of scientific research by improving effect size estimation.