How to reconcile prediction profiler confidence intervals with parameter estimates for mixture design
I have an mixture experiment with four components. It's a custom design of 16 runs with no replication that started with a model that included interactions of two factors and three components. The mixture constraint is that the four components sum to 1.0. The reduced model from the data has only the four main effects as statistically significant (p<.0001). The prediction profiler plots show 95% ...