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Sample size estimation and power analysis for clinical research studies
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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409926/ https://www.ncbi.nlm.nih.gov/pubmed/22870008 http://dx.doi.org/10.4103/0974-1208.97779 |
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author | Suresh, KP Chandrashekara, S |
author_facet | Suresh, KP Chandrashekara, S |
author_sort | Suresh, KP |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3409926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-34099262012-08-06 Sample size estimation and power analysis for clinical research studies Suresh, KP Chandrashekara, S J Hum Reprod Sci Review Article 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. Medknow Publications & Media Pvt Ltd 2012 /pmc/articles/PMC3409926/ /pubmed/22870008 http://dx.doi.org/10.4103/0974-1208.97779 Text en Copyright: © Journal of Human Reproductive Sciences http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Suresh, KP Chandrashekara, S Sample size estimation and power analysis for clinical research studies |
title | Sample size estimation and power analysis for clinical research studies |
title_full | Sample size estimation and power analysis for clinical research studies |
title_fullStr | Sample size estimation and power analysis for clinical research studies |
title_full_unstemmed | Sample size estimation and power analysis for clinical research studies |
title_short | Sample size estimation and power analysis for clinical research studies |
title_sort | sample size estimation and power analysis for clinical research studies |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409926/ https://www.ncbi.nlm.nih.gov/pubmed/22870008 http://dx.doi.org/10.4103/0974-1208.97779 |
work_keys_str_mv | AT sureshkp samplesizeestimationandpoweranalysisforclinicalresearchstudies AT chandrashekaras samplesizeestimationandpoweranalysisforclinicalresearchstudies |