Tips for troublesome sample-size calculation
Open accessAbstract
Properly set sample size is one of the important factors for scientific and persuasive research. The sample size that can guarantee both clinically significant differences and adequate power in the phenomena of interest to the investigator, without causing excessive financial or medical considerations, will always be the object of concern. In this paper, we reviewed the essential factors for sample size calculation. We described the primary endpoints that are the main concern of the study and the basis for calculating sample size, the statistics used to analyze the primary endpoints, type I error and power, the effect size and the rationale. It also included a method of calculating the adjusted sample size considering the dropout rate inevitably occurring during the research. Finally, examples regarding sample size calculation that are appropriately and incorrectly described in the published papers are presented with explanations.
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In general, sample size calculation and power analysis are determined by effect size, power (1-β), significance level (α), and type of statistical analysis.
“In general, the sample size calculation and power analysis are determined by the following factors: effect size, power (1-β), significance level (α), and type of statistical analysis [1,7].”
From Sample size determination and power analysis using the G*Power software (2021) · cites this paper as [1]
The need for an appropriate sample size calculation has become a major trend in research.
“Although there have been debates on sample size calculation and power analysis [3,4,6], the need for an appropriate sample size calculation has become a major trend in research [1,2,7-11].”
From Sample size determination and power analysis using the G*Power software (2021) · cites this paper as [1]
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Cites
T test as a parametric statistic
Kim, T. K. (2015) · Korean Journal of Anesthesiology · doi:10.4097/kjae.2015.68.6.540 · Cited by 1,447 · see citing works
Self-citationCentral limit theorem: the cornerstone of modern statistics
Kwak, S. G., & Kim, J. H. (2017) · Korean Journal of Anesthesiology · doi:10.4097/kjae.2017.70.2.144 · Cited by 1,062 · cited 4× · see citing works
“Jae Hong Park (Writing – original draft) Junyong In (Conceptualization; Writing – review & editing) Hyun Kang (Methodology; Supervision) Jong Hae Kim (Data curation) Tae Kyun Kim (Data curation; Methodology) Eun Jin Ahn (Data curation) Dong Kyu Lee (Conceptualization; Data curation) Sangseok Lee (Data curation; Method…”
MethodInfluentialSelf-citationSignificance, Errors, Power, and Sample Size: The Blocking and Tackling of Statistics
Mascha, E. J., & Vetter, T. R. (2018) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000002741 · Cited by 240 · see citing works
More about the basic assumptions of t-test: normality and sample size
Kim, T. K., & Park, J. H. (2019) · Korean Journal of Anesthesiology · doi:10.4097/kja.d.18.00292 · Cited by 208 · cited 6× · see citing works
“Tips for troublesome sample-size calculation Junyong In1, Hyun Kang2, Jong Hae Kim3, Tae Kyun Kim4, Eun Jin Ahn5, Dong Kyu Lee6, Sangseok Lee7, Jae Hong Park8 Department of Anesthesiology and Pain Medicine, 1Dongguk University Ilsan Hospital, Goyang, 2Chung-Ang University College of Medicine, Seoul, 3Daegu Catholic Un…”
BackgroundMethodInfluentialSelf-citationNahm, F. S. (2015) · Hanyang Medical Reviews · doi:10.7599/hmr.2015.35.1.40 · Cited by 43 · see citing works
In, C.-B., Cho, S., Lee, S., et al. (2018) · Korean Journal of Anesthesiology · doi:10.4097/kja.d.18.00121 · Cited by 17 · see citing works
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Sample size determination and power analysis using the G*Power software
Kang, H. (2021) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2021.18.17 · Cited by 2,572 · see citing works
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- Authors
- In, J., Kang, H., Kim, J. H., Kim, T. K., Ahn, E. J., Lee, D. K., Lee, S., & Park, J. H.
- Affiliations
- Dongguk University Ilsan Hospital (KR)
- Chung-Ang University (KR)
- Pusan National University Yangsan Hospital (KR)
- Inje University Seoul Paik Hospital (KR)
- Korea University (KR)
- Inje University (KR)
- Inje University Haeundae Paik Hospital (KR)
- Corresponding author
- Park, Jae Hong
- ORCID
- Venue
- Korean Journal of Anesthesiology
- Published
- 2020-04-01
- Volume
- 73
- Issue
- 2
- Pages
- 114-120
- ISSN
- 0302-5780 (ISSN-L)
- 2005-6419
- 2005-7563
- PMC
- PMC7113158
- OpenAlex
- W3013623720
- Cited by
- 55
- References
- 6
- Citations by year
- 2026: 9 · 2025: 14 · 2024: 11 · 2023: 10 · 2022: 3 · 2021: 5 · 2020: 3
- FWCI
- 3.70
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-05-25)
- Open access
- diamond
- doi.org
- Licence
- Locations
- Korean Journal of Anesthesiology (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- sample size determination, statistical power, type I error, effect size, primary endpoint, dropout rates, clinical significance, research design
- MeSH terms
- Biometry, Humans, Patient Dropouts, Research Design, Sample Size
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