| Abstract: | ComDim analysis was designed to assess the relationships between individuals and variables within a multiblock setting where several variables, organized in blocks, are measured on the same individuals. An overview of this method is presented together with some of its properties. Furthermore, we discuss a new extension of the method of analysis to the case of (K+1) datasets. More precisely, the aim is to explore the relationships between a response dataset and K other datasets. An illustration of this latter strategy of analysis on the basis of a case study involving Time Domain ‐ Nuclear Magnetic Resonance data is outlined and the outcomes are compared with those of Multiblock Partial Least Squares regression. |
