Treatments of non-metric variables in partial least squares and principal component analysis

Abstract

This paper reviews various treatments of non-metric variables in Partial Least Squares (PLS) and Principal Component Analysis (PCA) algorithms. The performance of different treatments is compared in the extensive simulation study under several typical data generating processes and recommendations are made. An application of PLS and PCA algorithms with non-metric variables to the generation of a wealth index is considered