Multivariate analysis of multiblock and multigroup data

•We outline new properties of multigroup Principal Component Analysis.•We extend this method of analysis to multiblock and multigroup data.•We illustrate the proposed method on real dataset.

We address the problem of analyzing one or several blocks of variables measured on the same individuals which are a priori divided into several groups. In this framework, we focus on the within-group analysis. For the case of a single dataset, we consider multigroup Principal Component Analysis proposed by several authors (Levin [18]; Krzanowski [16]; Kiers and Ten Berge [13]). A new optimization criterion which characterizes this method and an extension to the case of multiblock datasets are presented. The method is illustrated on the basis of a dataset pertaining to sensory analysis.