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Obtaining evidence for no effect
Version 2 2023-06-12, 08:07
Version 1 2023-06-10, 01:20
journal contribution
posted on 2023-06-12, 08:07 authored by Zoltan DienesZoltan DienesObtaining evidence that something does not exist requires knowing how big it would be were it to exist. Testing a theory that predicts an effect thus entails specifying the range of effect sizes consistent with the theory, in order to know when the evidence counts against the theory. Indeed, a theoretically relevant effect size must be specified for power calculations, equivalence testing, and Bayes factors in order that the inferential statistics test the theory. Specifying relevant effect sizes for power, or the equivalence region for equivalence testing, or the scale factor for Bayes factors, is necessary for many journal formats, such as registered reports, and should be necessary for all articles that use hypothesis testing. Yet there is little systematic advice on how to approach this problem. This article offers some principles and practical advice for specifying theoretically relevant effect sizes for hypothesis testing.
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Publication status
- Published
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- Published version
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Collabra: PsychologyISSN
2474-7394Publisher
University of California PressExternal DOI
Issue
1Volume
7Page range
1-15Article number
a28202Department affiliated with
- Psychology Publications
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- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-10-08First Open Access (FOA) Date
2021-10-08First Compliant Deposit (FCD) Date
2021-10-07Usage metrics
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