Locally D-optimal designs for multistage models and heteroscedastic polynomial regression models

We consider the construction of locally D-optimal designs for a nonlinear, multistage model in which one observes a binary response variable with expected value P(x;θ)=H(θ0+θ1x+⋯+θkxk). Here H is any twice differentiable distribution function. Our results apply as well to heteroscedastic polynomial regression models, under mild conditions on the efficiency function.