AI 中文总结
研究在对实验对象重复测量时实验设计的分类与可视化问题，通过定义基于对象、测量及随机化策略的特征来澄清混淆，利用这些特征分类并借助哈斯图可视化实验设计。
AI 中文摘要
在涉及人类或动物的实验（如临床或临床前研究）中，通常会对实验对象进行多次测量。这可能包括随时间重复测量以追踪趋势、给予一系列治疗以比较个体内效果，或对每个对象取多个技术重复样本以获得更可靠的平均反应。然而，对于什么构成“重复测量”存在混淆。本文通过定义在多次评估对象时设计可能具有的特征来澄清这种混淆。这些特征基于对象是否为实验单位、实验单位是否被重复测量以及使用哪种随机化策略来划分。然后可利用这些特征对实验设计进行分类并用哈斯图可视化。
英文摘要
When running experiments that involve humans or animals, for example in clinical or pre-clinical research, it is often the case that multiple measurements are taken on the experimental subjects. This may involve measuring subjects repeatedly over time to track any trends, administering a sequence of treatments to compare their effects within-subject, or taking multiple technical replicate samples of each subject to obtain a more reliable average response. However, it appears that there is some confusion as to what constitutes a 'repeated measure' and what does not. This paper clarifies this confusion by defining characteristics a design may possess when the subjects are assessed multiple times. These characteristics are delineated based on whether the subjects are the experimental units, if the experimental units are measured repeatedly or not, and which randomisation strategy is used. Experimental designs can then be classified using these characteristics and visualised using Hasse diagrams.
