Population Power Curves in ASCA With Permutation Testing

IF 2.3 4区 化学 Q1 SOCIAL WORK Journal of Chemometrics Pub Date : 2024-08-27 DOI:10.1002/cem.3596
José Camacho, Michael Sorochan Armstrong
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Abstract

In this paper, we revisit the power curves in ANOVA simultaneous component analysis (ASCA) based on permutation testing and introduce the population curves derived from population parameters describing the relative effect among factors and interactions. The relative effect has important practical implications: The statistical power of a given factor depends on the design of other factors in the experiment and not only of the sample size. Thus, understanding the relative power in a specific experimental design can be extremely useful to maximize our capability of success when planning the experiment. In the paper, we derive relative and absolute population curves, where the former represent statistical power in terms of the normalized effect size between structure and noise, and the latter in terms of the sample size. Both types of population curves allow us to make decisions regarding the number and nature (fixed/random) of factors, their relationships (crossed/nested), and the number of levels and replicates, among others, in an multivariate experimental design (e.g., an omics study) during the planning phase of the experiment. We illustrate both types of curves through simulation.
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带有置换测试的 ASCA 人口功率曲线
在本文中,我们重新审视了基于置换检验的方差分析同时成分分析(ASCA)中的功率曲线,并引入了由描述因子间和交互作用间相对效应的群体参数导出的群体曲线。相对效应具有重要的实际意义:给定因素的统计能力取决于实验中其他因素的设计,而不仅仅是样本量。因此,了解特定实验设计中的相对效应对于我们在规划实验时最大限度地提高成功率非常有用。在本文中,我们推导了相对和绝对群体曲线,前者以结构和噪声之间的归一化效应大小表示统计能力,后者以样本量表示统计能力。这两类种群曲线都能让我们在实验计划阶段,就多元实验设计(如 omics 研究)中因子的数量和性质(固定/随机)、它们之间的关系(交叉/嵌套)、水平和重复的数量等做出决策。我们通过模拟来说明这两种类型的曲线。
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来源期刊
Journal of Chemometrics
Journal of Chemometrics 化学-分析化学
CiteScore
5.20
自引率
8.30%
发文量
78
审稿时长
2 months
期刊介绍: The Journal of Chemometrics is devoted to the rapid publication of original scientific papers, reviews and short communications on fundamental and applied aspects of chemometrics. It also provides a forum for the exchange of information on meetings and other news relevant to the growing community of scientists who are interested in chemometrics and its applications. Short, critical review papers are a particularly important feature of the journal, in view of the multidisciplinary readership at which it is aimed.
期刊最新文献
Issue Information Issue Information Resampling as a Robust Measure of Model Complexity in PARAFAC Models Population Power Curves in ASCA With Permutation Testing A Non‐Linear Model for Multiple Alcohol Intakes and Optimal Designs Strategies
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