REVIEW ARTICLE
Year : 2012  |  Volume : 5  |  Issue : 1  |  Page : 7-13

Sample size estimation and power analysis for clinical research studies

KP Suresh¹, S Chandrashekara^2
1 Department of Biostatistics, National Institute of Animal Nutrition and Physiology, Bangalore, India
² Department of Immunology and Reumatology, ChanRe Rheumatology and Immunology Center and Research, Bangalore, India

Correspondence Address:
K P Suresh
Scientist(ss), National Institute of Animal Nutrition and Physiology Adugodi, Bangalore-560030
India

Source of Support: None, Conflict of Interest: None

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Read associated Retraction: Sample size estimation and power analysis for clinical research studies: Retraction with this article

DOI: 10.4103/0974-1208.97779

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.

Keywords: Correlation, odds ratio, power, prevalence, survey, proportions, sample size

This has been retracted as the sections in the text have been directly copied from a previously published article, entitled, "Issues in outcomes research: An overview of randomization techniques for clinical trials," in pages 215-221, Issue 2, Vol. 45 of Journal of Athletic Training

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