Cited by 1,024Statistical Methods in EpidemiologyStatistical Methods in Clinical TrialsProbability and Statistical Research

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Sample size estimation and power analysis for clinical research studies

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Suresh, KP, Chandrashekara, S·2012·Journal of Human Reproductive Sciences

DOI 10.4103/0974-1208.97779PMC PMC3409926

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Abstract

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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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
ORCID: Suresh, KP
Chandrashekara, S
Venue: Journal of Human Reproductive Sciences
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2012-01
Volume: 5
Issue: 1
Pages: 7-13
ISSN: 0974-1208 (ISSN-L)
1998-4766
DOI: 10.4103/0974-1208.97779
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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Sample size estimation and power analysis for clinical research studies

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