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When small effects are impressive
Abstract
Effect size is becoming an increasingly popular measure of the importance of an effect, both in individual studies and in meta-analyses. However, a large effect size is not the only way to demonstrate that an effect is important. This article describes 2 alternative methodological strategies, in which importance is a function of how minimal a manipulation of the independent variable or how difficult-to-influence a dependent variable will still produce an effect. These methodologies demonstrate the importance of an independent variable or psychological process, even though they often yield effects that are small in statistical terms
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Small effects are impressive when the dependent variable is not expected to be easily influenced by the independent variable.
“Prentice and Miller (1992) argue that small effects are impressive when the dependent variable is not expected to be easily influenced by the independent variable.”
From Psychosocial functioning and the cortisol awakening response: meta-analysis, P-curve analysis, and evaluation of the evidential value in existing studies (2017) · cites this paper as Prentice and Miller (1992)
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“Given that our intervention was small and performed in a field setting, which carries more noise than a laboratory setting, having a modest effect is understandable and even promising (Prentice and Miller, 1992).”
Background
Metadata
- Authors
- Prentice, D. A., & Miller, D. T.
- Affiliations
- Princeton University (US)
- Venue
- Psychological Bulletin
- Published
- 1992-07
- Volume
- 112
- Issue
- 1
- Pages
- 160-164
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2011756420
- Cited by
- 1,008
- References
- 27
- Citations by year
- 2026: 32 · 2025: 34 · 2024: 21 · 2023: 33 · 2022: 38 · 2021: 37 · 2020: 56 · 2019: 48 · 2018: 50 · 2017: 45 · 2016: 45 · 2015: 45 · 2014: 41 · 2013: 40 · 2012: 49
- FWCI
- 12.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Bulletin (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- effect size, meta-analysis, cognitive processes
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