When should we use one-tailed hypothesis testing?
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Summary: 1. Although one‐tailed hypothesis tests are commonly used, clear justification for why this approach is used is often missing from published papers. 2. Here we suggest explicit questions authors should ask of themselves when deciding whether or not to adopt one‐tailed tests. 3. First, we suggest that authors should only use a one‐tailed test if they can explain why they are more interested in an effect in one direction and not the other. 4. We suggest a further requirement that adoption of one‐tailed testing requires an explanation why the authors would treat a large observed difference in the unexpected direction no differently from a difference in the expected direction that was not strong enough to justify rejection of the null hypothesis. 5. These justifications should be included in published works that use one‐tailed tests, allowing editors, reviewers and readers the ability to evaluate the appropriateness of the adoption of one‐tailed testing. 6. We feel that adherence to our suggestions will allow authors to use one‐tailed tests more appropriately, and readers to form their own opinion about such appropriateness when one‐tailed tests are used.
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The use of a one-sided test requires justification of why a treatment effect is only of interest when it is in a defined direction and why they would treat a large effect in the unexpected direction no differently from a nonsignificant difference.
“The use of a one-sided test requires justification of why a treatment effect is only of interest when it is in a defined direction and why they would treat a large effect in the unexpected direction no differently from a nonsignificant difference [43].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [43]
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Ferreira, H. M., da Silva, R. C., do Nascimento, F. S., Wenseleers, T., & Oi, C. A. (2022) · Chemoecology · doi:10.1007/s00049-022-00370-y · Cited by 13 · see citing works
Blakeslee, J. E., Miller, R., & Uretsky, M. C. (2022) · Children and Youth Services Review · doi:10.1016/j.childyouth.2022.106507 · Cited by 15 · see citing works
Dauwalter, D. C., Wenger, S. J., Gelwicks, K. R., & Fesenmyer, K. A. (2011) · Transactions of the American Fisheries Society · doi:10.1080/00028487.2011.587753 · Cited by 13 · see citing works
The Statistical Analysis of Small Data Sets
Neuhäuser, M., & Ruxton, G. D. (2024) · doi:10.1093/oso/9780198872979.001.0001 · Cited by 12 · see citing works
Self-citationKrohmer, K., Derntl, B., & Svaldi, J. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00851 · Cited by 12 · see citing works
Princen, S. A., Oystaeyen, A. V., Petit, C., van Zweden, J. S., & Wenseleers, T. (2019) · Behavioral Ecology · doi:10.1093/beheco/arz191 · Cited by 12 · see citing works
Methods for independently manipulating palatability and color in small insect prey
Winsor, A. M., Ihle, M., & Taylor, L. A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231205 · Cited by 12 · see citing works
The status and stigma consequences of mental illness labels, deviant behavior, and fear
Manago, B. N., & Mize, T. D. (2021) · Social Science Research · doi:10.1016/j.ssresearch.2021.102690 · Cited by 12 · see citing works
Lew, M. J. (2019) · Handbook of experimental pharmacology · doi:10.1007/164_2019_286 · Cited by 12 · see citing works
Gartrelle, G. M., HARDERSEN, P. S., Izawa, M. R. M., & Nowinski, M. C. (2021) · Icarus · doi:10.1016/j.icarus.2020.114295 · Cited by 12 · see citing works
Digital marketing, competitive advantage, marketing communication, social media, consumers
Nadányiová, M., Majerová, J., & Gajanová, Ľ. (2021) · Marketing and Management of Innovations · doi:10.21272/mmi.2021.4-08 · Cited by 11 · see citing works
- Authors
- Ruxton, G. D., & Neuhäuser, M.
- Affiliations
- University of Glasgow (GB)
- Koblenz University of Applied Sciences (DE)
- Corresponding author
- Ruxton, Graeme D.
- Venue
- Methods in Ecology and Evolution
- Publisher
- Wiley
- Published
- 2010-05-04
- Volume
- 1
- Issue
- 2
- Pages
- 114-117
- ISSN
- 2041-210X (ISSN-L)
- OpenAlex
- W1563749973
- Cited by
- 269
- References
- 11
- Citations by year
- 2026: 15 · 2025: 14 · 2024: 31 · 2023: 17 · 2022: 16 · 2021: 59 · 2020: 23 · 2019: 22 · 2018: 18 · 2017: 9 · 2016: 5 · 2015: 10 · 2014: 7 · 2013: 5 · 2012: 6
- FWCI
- 7.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Methods in Ecology and Evolution (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- null hypothesis significance testing, statistical reporting guidelines, research reproducibility
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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