With the help of Generalized Estimating Equations, we identify locally D-optimal crossover designs for generalized linear models. We adopt the variance of parameters of interest as the objective function, which is minimized using constrained optimization to obtain optimal crossover designs. In this case, the traditional general equivalence theorem could not be used directly to check the optimality of obtained designs. In this manuscript, we derive a corresponding general equivalence theorem for crossover designs under generalized linear models.

翻译：借助广义估计方程，我们识别了广义线性模型的局部D-最优交叉设计。采用感兴趣参数的方差作为目标函数，通过约束优化最小化该函数以获得最优交叉设计。在此情形下，传统的一般等价定理无法直接用于检验所得设计的最优性。本文推导了广义线性模型下交叉设计对应的广义等价定理。