Generalized Probit Model in Design of Dose Finding Experiments

Abstract

In clinical studies, continuous endpoints are very commonly seen. However, either for ease of interpretation or to simplify the reporting process, some continuous endpoints are often reported and (unfortunately) analyzed as binary or ordinal responses. We emphasize the usefulness of differentiation between response and utility functions and develop tools to build locally optimal designs for corresponding models. It is also shown that dichotomization of responses may lead to significant loss in statistical precision. We consider an example with two responses and one utility function. The generalization to a larger number of responses and utility functions is straightforward.