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Minimum Detectable Effects: A Simple Way to Report the Statistical Power of Experimental Designs
Abstract
This article describes a simple way to assess the statistical power of experimental designs. The approach presented is based on the concept of a minimum detectable effect, which, intuitively, is the smallest true impact that an experiment has a good chance of detecting. The article illustrates how to compute minimum detectable effects and how to apply this concept to the assessment of alternative experimental designs. Applications to impact estimators for both continuous and binary outcome measures are considered
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Cites
Statistical Power Analysis for the Behavioral Sciences
(1977) · doi:10.1016/c2013-0-10517-x · Cited by 2,457
Cited by
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Dong, N., & Maynard, R. (2013) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2012.673143 · Cited by 206
York, B. N., Loeb, S., & Doss, C. (2019) · Journal of Human Resources · doi:10.3368/jhr.54.3.0517-8756r · Cited by 155
HEATH, D., RINGGENBERG, M. C., SAMADI, M., & WERNER, I. M. (2023) · The Journal of Finance · doi:10.1111/jofi.13250 · Cited by 133
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Killewald, A. (2013) · Demography · doi:10.1007/s13524-012-0190-0 · Cited by 92
Metadata
- Authors
- Bloom, H. S.
- Venue
- Evaluation Review
- Publisher
- SAGE Publications
- Published
- 1995-10
- Volume
- 19
- Issue
- 5
- Pages
- 547-556
- ISSN
- 0145-4692 (ISSN-L)
- 0193-841X
- 1552-3926
- OpenAlex
- W2053520781
- Cited by
- 280
- References
- 1
- FWCI
- 0.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bloom, H. S. (1995). Minimum Detectable Effects: A Simple Way to Report the Statistical Power of Experimental Designs. Evaluation Review. https://doi.org/10.1177/0193841x9501900504
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
