One App to Rule Them All: A One-Stop Calculator and Guide for 95 Effect-Size Variants for Two-Group Comparisons of Central Tendency, Variability, Overlap, Dominance, and Distributional Tails

The prevalence of effect-size (ES) reporting has risen significantly, yet studies comparing two groups tend to rely exclusively on the Cohen’s d family of ESs. In this article, we aim to broaden the readers’ horizon of known ESs by introducing various ES families for two-group comparisons, including indices of standardized differences in central tendency, overlap, dominance, and differences in variability and distributional tails. We describe parametric and nonparametric estimators in each ES family and present an interactive web application (R Shiny) for computing these ESs and facilitating their application. This one-stop calculator allows for the computation of 95 applications of 67 unique ESs and their confidence intervals and various plotting options and provides detailed descriptions for each ES, making it a valuable resource for both self-guided exploration and instructor-led teaching. With this comprehensive guide and its companion app, we aim to improve the clarity and accuracy of ES reporting in research design that involves two-group comparisons.

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Publication Details

Journal
Advances in Methods and Practices in Psychological Science
Published
2025-04-01
DOI
https://doi.org/10.1177/25152459251323186
Citations
4
Primary Topic
Advanced Statistical Modeling Techniques
Type
article
Field-Weighted Citation Impact
5.95
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article

One App to Rule Them All: A One-Stop Calculator and Guide for 95 Effect-Size Variants for Two-Group Comparisons of Central Tendency, Variability, Overlap, Dominance, and Distributional Tails

Marton L. Gyimesi, Martin Voracek, Marco Del Giudice, Ulrich S. Tran et al.
4 citations
Advances in Methods and Practices in Psychological Science
Advanced Statistical Modeling Techniques
5.95
article

One App to Rule Them All: A One-Stop Calculator and Guide for 95 Effect-Size Variants for Two-Group Comparisons of Central Tendency, Variability, Overlap, Dominance, and Distributional Tails

Marton L. Gyimesi, Martin Voracek, Marco Del Giudice, Ulrich S. Tran, Victor Webersberger
article en
4 citations

Abstract

The prevalence of effect-size (ES) reporting has risen significantly, yet studies comparing two groups tend to rely exclusively on the Cohen’s d family of ESs. In this article, we aim to broaden the readers’ horizon of known ESs by introducing various ES families for two-group comparisons, including indices of standardized differences in central tendency, overlap, dominance, and differences in variability and distributional tails. We describe parametric and nonparametric estimators in each ES family and present an interactive web application (R Shiny) for computing these ESs and facilitating their application. This one-stop calculator allows for the computation of 95 applications of 67 unique ESs and their confidence intervals and various plotting options and provides detailed descriptions for each ES, making it a valuable resource for both self-guided exploration and instructor-led teaching. With this comprehensive guide and its companion app, we aim to improve the clarity and accuracy of ES reporting in research design that involves two-group comparisons.

Advances in Methods and Practices in Psychological ScienceVol. 8(2)
University of Vienna (AT), University of Trieste (IT)
Openalex Percentile: Top 4%
Advanced Statistical Modeling Techniques
5.95
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One App to Rule Them All: A One-Stop Calculator and Guide for 95 Effect-Size Variants for Two-Group Comparisons of Central Tendency, Variability, Overlap, Dominance, and Distributional Tails — Marton L. Gyimesi, Martin Voracek, et al. · Advances in Methods and Practices in Psychological Science (2025) | TGRS Research Map | TGRS