Being an ecologist, I routinely switch back and forth between JMP and PRIMER, but, with each update of JMP, I can do more in JMP (and therefore less need for PRIMER). However, PRIMER has a multivariate, distance matrix-based algorithm called "distance-based linear modeling" (DistLM) that essentially works like stepwise regression (model selection by minimizing BIC/AICc) though with a distance matrix as the input. It is great for those looking to find the best model to explain similarity and differences between samples in a multivariate framework. I feel like JMP already has distance matrix capacity AND stepwise regression, and, although I know this is much more complicated than univariate stepwise regression, I think it should be possible to develop this technique in JMP (as well as the more commonly used PERMANOVA). Actually, it doesn't need to be DistLM, just any multivariate incarnation of stepwise regression. Pleassssssseeeeee.