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| REVIEW ARTICLE |
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| Year : 2012 |
Volume
: 5 | Issue : 1 | Page
: 7-13 |
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Sample size estimation and power analysis for clinical research studies
KP Suresh1, S Chandrashekara2
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  | Check |
DOI: 10.4103/0974-1208.97779
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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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