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Sample size estimation and power analysis for clinical research studies
Open accessAbstract
Determining the optimal sample size for a study assures an adequate power to detect statistical significance. Hence, it is a critical step in the design of a planned research protocol. Using too many participants in a study is expensive and exposes more number of subjects to procedure. Similarly, if study is underpowered, it will be statistically inconclusive and may make the whole protocol a failure. This paper covers the essentials in calculating power and sample size for a variety of applied study designs. Sample size computation for single group mean, survey type of studies, 2 group studies based on means and proportions or rates, correlation studies and for case-control for assessing the categorical outcome are presented in detail.
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“Understanding rates of eligibility in a population helps power and inform future trials, 26”
From Wellbeing After Stroke (WAterS): Feasibility Testing of a Co-developed Acceptance and Commitment Therapy Intervention to Support Psychological Adjustment After Stroke. (2024) · cites this paper as [26]
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Metadata
- Authors
- Suresh, K., & Chandrashekara, S.
- Affiliations
- National Institute of Animal Nutrition and Physiology (IN)
- Department of Immunology and Reumatology, ChanRe Rheumatology and Immunology Center and Research, Bangalore, India
- Venue
- Journal of Human Reproductive Sciences
- Published
- 2012-01
- Volume
- 5
- Issue
- 1
- Pages
- 7-13
- ISSN
- 0974-1208 (ISSN-L)
- 1998-4766
- PMC
- PMC3409926
- OpenAlex
- W2038287973
- Cited by
- 1,024
- References
- 20
- Citations by year
- 2026: 47 · 2025: 94 · 2024: 115 · 2023: 98 · 2022: 127 · 2021: 118 · 2020: 85 · 2019: 65 · 2018: 62 · 2017: 56 · 2016: 52 · 2015: 67 · 2014: 31 · 2013: 6
- FWCI
- 31.52
- Type
- journal article
- Language
- en
- Status
- Retracted
- Update notices
- retraction (2015-07-01)
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- Journal of Human Reproductive Sciences (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- sample size determination, statistical power, clinical research design, two-group comparison, proportion, rates, correlation, case-control study, categorical outcomes, survey studies
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