On optimal allocation of treatment/condition variance in principal component analysis
Applications
2018-04-20 v1 Methodology
Abstract
The allocation of a (treatment) condition-effect on the wrong principal component (misallocation of variance) in principal component analysis (PCA) has been addressed in research on event-related potentials of the electroencephalogram. However, the correct allocation of condition-effects on PCA components might be relevant in several domains of research. The present paper investigates whether different loading patterns at each condition-level are a basis for an optimal allocation of between-condition variance on principal components. It turns out that a similar loading shape at each condition-level is a necessary condition for an optimal allocation of between-condition variance, whereas a similar loading magnitude is not necessary.
Keywords
Cite
@article{arxiv.1804.07079,
title = {On optimal allocation of treatment/condition variance in principal component analysis},
author = {André Beauducel and Norbert Hilger},
journal= {arXiv preprint arXiv:1804.07079},
year = {2018}
}