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Beyond reporting statistical significance: Identifying informative effect sizes to improve scientific communication.

Hanel, Paul HP and Mehler, David MA (2019) 'Beyond reporting statistical significance: Identifying informative effect sizes to improve scientific communication.' Public Understanding of Science, 28 (4). 468 - 485. ISSN 0963-6625

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Abstract

Transparent communication of research is key to foster understanding within and beyond the scientific community. An increased focus on reporting effect sizes in addition to p value-based significance statements or Bayes Factors may improve scientific communication with the general public. Across three studies ( N = 652), we compared subjective informativeness ratings for five effect sizes, Bayes Factor, and commonly used significance statements. Results showed that Cohen's U3 was rated as most informative. For example, 440 participants (69%) found U3 more informative than Cohen's d, while 95 (15%) found d more informative than U3, with 99 participants (16%) finding both effect sizes equally informative. This effect was not moderated by level of education. We therefore suggest that in general, Cohen's U3 is used when scientific findings are communicated. However, the choice of the effect size may vary depending on what a researcher wants to highlight (e.g. differences or similarities).

Item Type: Article
Uncontrolled Keywords: Cohen’s d, Cohen’s U3, effect size, scientific communication, statistical communication, statistical significance
Divisions: Faculty of Science and Health > Psychology, Department of
Depositing User: Elements
Date Deposited: 01 Mar 2021 20:25
Last Modified: 01 Mar 2021 20:25
URI: http://repository.essex.ac.uk/id/eprint/29784

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