From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis
Methodology
2026-05-20 v2
Abstract
ANOVA Simultaneous Component Analysis (ASCA) is the current state-of-theart chemometric tool for analyzing and interpreting high-dimensional experimental data from a Design of Experiment (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE. This tutorial review recommends best practices for using ASCA, building upon the long-established combination of ANOVA and DoE theory developed over the last century. These recommendations are grounded in a comprehensive literature review and illustrated through a guiding example.
Keywords
Cite
@article{arxiv.2604.19265,
title = {From design of experiments to analysis of variance of multivariate data: a tutorial review on ANOVA simultaneous component analysis},
author = {José Camacho and Jokin Ezenarro and Daniel Schorn-García and Johan A. Westerhuis},
journal= {arXiv preprint arXiv:2604.19265},
year = {2026}
}