Model robust designs for survival trials

Abstract

The exponential-based proportional hazards model is often assumed in time- to-event experiments but may only approximately hold. We consider deviations in different neighbourhoods of this model that include other widely used paramet- ric proportional hazards models and we further assume that the data are subject to censoring. Minimax designs are then found explicitly based on criteria corre- sponding to classical c- and D-optimality. We provide analytical characterisations of optimal designs which, unlike optimal designs for related problems in the litera- ture, have finite support and thus avoid the issues of implementing a density-based design in practice. Finally, our designs are compared with the balanced design that is traditionally used in practice, and recommendations for practitioners are given.

Description

Table of contents

Keywords

proportional hazards models, Type-I censoring, c-optimality, D-optimality, minimax optimal designs

Citation