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用更少的钱获得更多的权力:统计,权力和成本分析,解释同组友实验中的集群内相关性
1Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
概括
在动物实验中,集群内相关性可能导致错误的阳性结果. 使用线性混合模型计算这种相关性可以提高统计准确性,降低成本并最大限度地减少动物使用.
科学领域:
- * 生物统计学
- *实验室动物科学 *实验室动物科学
- * * 实验设计设计
背景情况:
- * 在研究中,同居的动物可以由于集群内相关性而表现出相关的结果.
- *在同组友实验中忽视集群内相关性导致伪复制,并增加了假阳性结果.
- *本期反映了在人类研究中的集群随机试验中发现的挑战.
研究的目的:
- * 提供关于统计计算同组友实验中的集群内相关性的教程.
- * 为了证明效果大小和样本大小计算,以获得适当的实验功率.
- *强调减轻集群内相关性的实验设计的效率和成本效益.
主要方法:
- *使用线性混合模型,将子标识符作为独立变量.
- * 执行功率分析,包括效果大小和样本大小计算.
- * 进行成本分析,比较不同的实验设计.
- *使用JASP,R和SAS软件进行统计分析.
主要成果:
- *考虑到集群内相关性,可以减少假阳性的统计错误.
- * 具有更多子和更少动物的实验设计在统计学上更高效 (更高的功率).
- *优化设计可以减少动物数量,与动物研究的3R保持一致.
- *成本分析表明,每动物数量较少的子通常总体较便宜.
结论:
- *正确考虑集群内相关性对于同组友实验中的准确统计分析至关重要.
- *高效的实验设计提高了统计能力,降低了成本,并尽量减少了动物使用.
- *所介绍的方法提供了一种实际的方法,以提高动物研究的严谨性和道德性.
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