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临床研究的样本量估计与效能分析。

Sample size estimation and power analysis for clinical research studies.

作者信息

Suresh Kp, Chandrashekara S

机构信息

Department of Biostatistics, National Institute of Animal Nutrition and Physiology, Bangalore, India.

出版信息

J Hum Reprod Sci. 2012 Jan;5(1):7-13. 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.

摘要

确定一项研究的最佳样本量可确保有足够的检验效能来检测统计学显著性。因此,这是计划研究方案设计中的关键一步。在一项研究中使用过多参与者成本高昂,且会使更多受试者暴露于研究程序。同样,如果研究效能不足,在统计学上就无法得出结论,可能会导致整个方案失败。本文涵盖了各种应用研究设计中计算检验效能和样本量的要点。详细介绍了单组均值、调查类研究、基于均值以及比例或率的两组研究、相关性研究以及用于评估分类结局的病例对照研究的样本量计算方法。

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