Use of Two-Block Partial Least-Squares to Study Covariation in Shape

Abstract

The relatively new two-block partial least-squares method for analyzing the covariance between two sets of variables is described and contrasted with the well-known method of canonical correlation analysis. Their statistical properties, type of answers, and visualization techniques are discussed. Examples are given to show its usefulness in comparing two sets of variables--especially when one or both of the sets of variables are shape variables from a geometric morphometric study.