Choice of second-order response surface designs for logistic and Poisson regression models. (15th October 2009) - Johnson, Rachel T.; Montgomery, Douglas C.
Response surface methodology is widely used for process development and optimisation, product design, and as part of the modern framework for robust parameter design. For normally distributed responses, the standard second-order designs such as the central composite design and the Box-Behnken design have relatively high D and G efficiencies. In situations where these designs are inappropriate, standard computer software can be used to construct D-optimal and I-optimal designs for fitting second-order models. When the response distribution is either binomial or Poisson, the choice of an appropriate design is not as straightforward. We illustrate the construction of D-optimal second-order designs for these situations and show that they are considerably better choices than the standard designs. We present an example applying this approach to optimisation of an etching process.