When analyzing experimental chemical data, it is often necessary to incorporate the structure of the study design into the chemometric/statistical models to effectively address the research questions of interest. ANOVA-Simultaneous Component Analysis (ASCA) is one of the most prominent methods to include such information in the quantitative analysis of multivariate data, especially when the number of variables is large. This tutorial review intends to explain in a simple way how ASCA works, how it is operated and how to correctly interpret ASCA results, with approachable mathematical and visual descriptions. Two examples are given: the first, a simulated chemical reaction, serves to illustrate the ASCA steps and the second, from a real chemical ecology data set, the interpretation of results. An overview of methods closely related to ASCA is also provided, pointing out their differences and scope, to give a wide-ranging picture of the available options to build multivariate models that take experimental design into account.

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ANOVA 同时分量分析：教程回顾

在分析实验化学数据时，通常需要将研究设计的结构纳入化学计量/统计模型，以有效解决感兴趣的研究问题。ANOVA-Simultaneous Component Analysis (ASCA) 是将此类信息包含在多变量数据的定量分析中的最突出方法之一，尤其是当变量数量很大时。本教程回顾旨在以通俗易懂的数学和视觉描述，以简单的方式解释 ASCA 的工作原理、操作方式以及如何正确解释 ASCA 结果。给出了两个例子：第一个，模拟化学反应，用于说明 ASCA 步骤，第二个，来自真实的化学生态数据集，结果的解释。