Hierarchical multiblock PLS and PC models for easier model interpretation and as an alternative to variable selection
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In multivariate PLS (partial least square projection to latent structures) and PC (principal component) models with many variables, plots and lists of b loadings, coefficients, VIPs, etc. become messy and results are difficult to interpret. There is then a strong temptation to reduce the variables to a smaller, more manageable number. This reduction of variables, however, often removes information, makes the interpretation misleading and seriously increases the risk of spurious models.