It's as Jesper said. When we do a DoE and build a model, we really are getting the coefficients in the model terms that we've requested from JMP. For example, in the custom design, if I I have only three factors x1 x2 and x3, I might decide to include only specific terms in my model, based on my understanding of the physics, chemistry and mechanics of my system. I might, for example, chose to make my model like this: y = a + b1*x1 + b2 *x2 + b3*x3 + c1*x1*x1 + d12*x1*x3 In my notation, a is the constant (intercept) term, the b terms are coefficients of the linear terms, the c terms are the quadratic terms and the d terms are the interaction terms. I've decide on a model with the linear (main effects) terms, a quadratic effect in x1, and an x1, x3 interaction. These coefficients can take on either positive or negative values. The magnitude of each parameter estimate that JMP displays tells us the relative strength of the term's contribution to the response and the sign tells us in which direction that response operates as we increase the factor settings. In the situation you describe, increasing x makes an increase in the linear contribution to the response, but makes a negative increase (decrease) in the quadratic contribution to the response. Most times, the magnitude of these coefficients will decrease as you go from first-order (linear) terms to second order (quadratic and interaction terms), but not always.
... View more