4.7 Article

Approaches to Sample Size Determination for Multivariate Data: Applications to PCA and PLS-DA of Omics Data

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 15, Issue 8, Pages 2379-2393

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b01029

Keywords

loading estimation; covariance estimation; eigenvalue distribution; random matrix theory; hypothesis testing; dimensionality; multivariate analysis; power analysis

Funding

  1. European Commission [305340]

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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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