metaConvert: an automatic suite for estimation of 11 different effect size measures and flexible conversion across
Corentin J Gosling1,2,3, Samuele Cortese3,4,5,6,7, Marco Solmi3,8,9,10,11,12
1Université Paris Nanterre, Laboratoire DysCo, Nanterre, France.
Research Synthesis Methods
|February 2, 2026
Summary
Estimating effect sizes is crucial in science but can be challenging. The metaConvert R package and web tool simplify calculating and converting various effect size measures, improving accuracy for researchers.
Area of Science:
- Biostatistics
- Quantitative Research Methods
- Life Sciences
Background:
- Accurate estimation of effect sizes is fundamental for scientific research.
- Calculating and converting between different effect size measures can be complex and prone to errors.
Purpose of the Study:
- To introduce metaConvert, an R package and web tool designed to simplify effect size calculation and conversion.
- To provide a flexible and accurate solution for researchers across disciplines.
Main Methods:
- The metaConvert R package utilizes over 120 formulas for effect size conversion.
- It supports conversion to multiple common effect size metrics including Cohen's d, Hedges' g, odds ratio, and correlation coefficients.
- A user-friendly, browser-based graphical interface is available at https://metaconvert.org/ for non-R users.
Main Results:
- metaConvert automates the calculation and conversion of numerous effect size measures.
- The tool accommodates a wide range of input data types for conversion.
- Both R users and non-R users can access the functionality through the package or the web interface.
Conclusions:
- metaConvert enhances the ease and accuracy of effect size estimation in scientific research.
- This tool is valuable for researchers in life sciences and other fields requiring effect size analysis.
- The package and interface aim to reduce the complexity and potential errors in effect size calculations.
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