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A Mean Difference is an Effect Size

Pierre Dragicevic 1
1 AVIZ - Analysis and Visualization
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique
Abstract : Methodologists urge us to report effect sizes, but rarely explain what they mean by “effect size”. This can lead to counterproductive disputes about terminology. There is a narrow sense and a broad sense of the term “effect size”. The narrow sense refers to a family of unitless measures such as Cohen’s d, while the broad sense refers to any measure of interest, such as a mean difference in completion time expressed in seconds. Researchers in meta-analysis often use the narrow sense, while methodologists focusing on transparency in reporting generally prefer the broad sense. Researchers from the first group sometimes claim that those from the second group are misusing the term. They are not. The broad sense is older than the narrow one and even Jacob Cohen, who co-founded meta-analysis and popularized the term “effect size”, defined it broadly. It is OK to call a mean difference an effect size. When necessary, the term “effect size” can be easily made crisper with the widely-used qualifiers “standardized” and “unstandardized ” (or “simple”).
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Contributor : Pierre Dragicevic <>
Submitted on : Thursday, July 23, 2020 - 11:43:44 AM
Last modification on : Saturday, May 1, 2021 - 3:47:03 AM
Long-term archiving on: : Tuesday, December 1, 2020 - 5:25:46 AM


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  • HAL Id : hal-02905210, version 1


Pierre Dragicevic. A Mean Difference is an Effect Size. [Research Report] RR-9354, Inria Saclay Ile de France. 2020, pp.1-12. ⟨hal-02905210⟩



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