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最佳(但常被忽视)实践:有力研究的样本量规划。

Best (but oft forgotten) practices: sample size planning for powerful studies.

机构信息

Department of Psychology, Arizona State University, Tempe, AZ.

出版信息

Am J Clin Nutr. 2019 Aug 1;110(2):280-295. doi: 10.1093/ajcn/nqz058.


DOI:10.1093/ajcn/nqz058
PMID:31131390
Abstract

Given recent concerns regarding replicability and trustworthiness in several areas of science, it is vital to encourage researchers to conduct statistically rigorous studies. Achieving a high level of statistical power is one particularly important domain in which researchers can improve the quality and reproducibility of their studies. Although several factors influence statistical power, appropriate sample size planning is often under the control of the researcher and can result in powerful studies. However, the process of conducting sample size planning to achieve a specified level of desired statistical power is often complex and the literature can be difficult to navigate. This article aims to provide an approachable overview of statistical power and sample size planning, with emphasis on why statistical power is important for high-quality science. Thorough examples relevant to nutrition researchers are included to illustrate the process of sample size planning. Special consideration is also given to issues that may arise when conducting sample size planning in practice. The overarching goal is to provide nutrition researchers with the tools and expertise needed to conduct effective sample size planning for future studies.

摘要

鉴于最近人们对科学的几个领域的可重复性和可信度表示担忧,鼓励研究人员进行统计学上严谨的研究至关重要。在统计学功效这一特别重要的领域,研究人员可以提高其研究的质量和可重复性。尽管有几个因素会影响统计学功效,但适当的样本量规划通常在研究人员的控制之下,可以得出有力的研究结果。然而,为达到指定的期望统计学功效水平而进行样本量规划的过程通常很复杂,文献也很难理解。本文旨在提供一个通俗易懂的统计学功效和样本量规划概述,重点介绍为什么统计学功效对高质量科学很重要。文中包含了与营养研究人员相关的透彻示例,以说明样本量规划的过程。此外,还特别考虑了在实际进行样本量规划时可能出现的问题。总体目标是为营养研究人员提供进行未来研究的有效样本量规划所需的工具和专业知识。

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