Use Fit Model with the Salt in Popcorn.jmp sample data to fit the ordinal taste test to the surface effect of salt. Use Taste Test as Y. Highlight Salt in the Select Columns box, and then select Macros > Response Surface.
The report shows how the quadratic model fits the response probabilities. The curves, instead of being shifted logistic curves, become a folded pile of curves where each curve achieves its optimum at the same point. The critical value is at Mean(X)–0.5 *b1/b2 where b1 is the linear coefficient and b2 is the quadratic coefficient. This formula is for centered X. From the Parameter Estimates table, you can compute the optimum as 1.5 - 0.5* (0.5637/1.3499) = 1.29 teaspoons of salt.
Ordinal Logistic Fit for Salt in Popcorn.jmp
The parameter estimates for Salt and Salt*Salt become the coefficients used to find the critical value. Although it appears as a minimum, it is only a minimum with respect to the probability curves. It is really a maximum in the sense of maximizing the probability of the highest response. The Solution portion of the report is shown under Response Surface in Ordinal Logistic Fit for Salt in Popcorn.jmp, where 1.29 is shown under Critical Value.