Abstract: We consider the maximum variance optimality criterion of Elfving (1959) in the context of (nonlinear) response models. Some practical guidelines for the construction of minimax optimal designs are given. In some cases this criterion yields one point designs as a consequence of different scales of the elements in the Fisher information matrix. As an alternative a ``standardized'' maximum variance criterion is introduced and applied to the calculation of efficient designs. The results are illustrated for binary response models and it is demonstrated that in these models standardized minimax optimality should be prefered to ordinary minimax optimality.
Key words and phrases: Binary response models, maximum variance criterion, nonlinear regression models, optimal design, standardized variances.