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. 2012 Jan;5(1):7-13.
doi: 10.4103/0974-1208.97779.

Sample size estimation and power analysis for clinical research studies

Kp Suresh  1 , S Chandrashekara
Affiliations

Sample size estimation and power analysis for clinical research studies

Kp Suresh et al. J Hum Reprod Sci. 2012 Jan.

Retraction in

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; proportions; sample size; survey.

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Conflict of interest statement

Conflict of Interest: None declared.

References

    1. Shuster JJ. Boca Raton, FL: CRC Press; 1990. Handbook of sample size guidelines for clinical trials.
    1. Altman DG. London, UK: Chapman and Hall; 1991. Practical statistics for Medical Research.
    1. Wittes J. Sample size calculations for randomized controlled trials. Epidemiol Rev. 2002;24:39–53. - PubMed
    1. Desu M, Raghavarao D. Boston, MA: Academic Press, Inc; 1990. Sample size methodology.
    1. Agresti A. New York: John Wilely and Sons; 1990. Categorical data analysis.

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