Mixture Experiments provide a foundation to optimize the predicted response basedon blends of different components . Parody and Edwards (2006) gave a method of inference on the expected response of a 2nd-order rotatable design, utilizing a simulation-based critical point to give substantially sharper intervals when compared to the simultaneous confidence intervals provided by Sa and Edwards (1993). Here, we begin with discussing the theory of mixture experiments and pseudocomponents. Then we move on to review the literature of simulation-based methods forgenerating critical points and visualization techniques of general response surface designs. Next, we develop the simulation-based technique for a {q, 2} Simplex-Lattice Design and visualize the simulation-based confidence intervals for the expected improvement in response based on two examples. Finally, we compare theefficiency of the simulation-based critical points relative to Scheffé’s adaptation ofcritical points for the general response surface. We conclude by providing an efficiency table and demonstrate superiority of the simulation-based method over the Scheffé’s adaptation on the basis of sample size savings.

Publication Date


Document Type


Student Type


Degree Name

Applied Statistics (MS)

Department, Program, or Center

School of Mathematical Sciences (COS)


Robert Parody


RIT – Main Campus