单变量
多元统计
主成分分析
多元分析
偏最小二乘回归
样本量测定
样品(材料)
线性判别分析
统计
计算机科学
数据挖掘
人工智能
模式识别(心理学)
数学
色谱法
化学
作者
Edoardo Saccenti,Marieke E. Timmerman
标识
DOI:10.1021/acs.jproteome.5b01029
摘要
Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA.
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