How can Prediction Profiler help us understand a model?
May 27, 2016 8:31 AM
| Last Modified: Aug 18, 2020 1:50 PM
In his Advanced Mastering JMP 12 webcast, Using Generalized Regression in JMP Pro to Create Robust Linear Models, Brady Brady explains that interactively sliding factor values on the Prediction Profiler gives a visual way to see how changing one factor setting impacts the response as well as impacts the other factors in the model. If there are cross-terms in the model, when one term changes, changes in curve slope or shape of another term helps easily identify the interaction effects or cross-product effects in the model.