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在不增加样本量的情况下提高检验效能的四种简单方法。

Four simple ways to increase power without increasing the sample size.

作者信息

Lazic Stanley E

机构信息

Innovative Medicines and Early Development Biotech Unit, AstraZeneca, UK.

出版信息

Lab Anim. 2018 Dec;52(6):621-629. doi: 10.1177/0023677218767478. Epub 2018 Apr 8.

Abstract

Underpowered experiments have three problems: true effects are harder to detect, the true effects that are detected tend to have inflated effect sizes and as power decreases so does the probability that a statistically significant result represents a true effect. Many biology experiments are underpowered and recent calls to change the traditional 0.05 significance threshold to a more stringent value of 0.005 will further reduce the power of the average experiment. Increasing power by increasing the sample size is often the only option considered, but more samples increases costs, makes the experiment harder to conduct and is contrary to the 3Rs principles for animal research. We show how the design of an experiment and some analytical decisions can have a surprisingly large effect on power.

摘要

效能不足的实验存在三个问题

真实效应更难被检测到,所检测到的真实效应往往具有夸大的效应量,并且随着效能降低,具有统计学显著性的结果代表真实效应的概率也会降低。许多生物学实验的效能不足,最近将传统的0.05显著性阈值更改为更严格的0.005的呼声将进一步降低一般实验的效能。通过增加样本量来提高效能通常是唯一被考虑的选择,但更多的样本会增加成本,使实验更难进行,并且违背了动物研究的3R原则。我们展示了实验设计和一些分析决策如何能对效能产生惊人的巨大影响。

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