Good fraction of space, but low power of DoE

[#1]

Hello JMP community,

I am creating a DoE design with 2 continuous, 1 categorical (6 levels) and 1 categorical (2 levels). When I create a D-optimal design for this study, I see that the power for detecting the interactions that I am interested is quite low (Anticipated coefficient = 5, Power =0.61). However, the fraction of design plot looks quite good. 95% of the fraction of space lies below the prediction variance of 1.0.

Can you please explain why the fraction of design plot is good while the power of the model is quite low?

[#2]

Important considerations for the power are the number of runs and the actual design. You did not state either, so I created a design for the same factors and model using the default number of runs (25). The power in this case is better than what you showed while using the same anticipated coefficients.

I am not sure what you expected for the relative prediction variance in this case.