Model robust designs for survival trials

Model robust designs for survival trials

The exponential-based proportional hazards model is often assumed in timeto-event experiments but may only approximately hold. We consider deviations in different neighbourhoods of this model that include other widely used parametric proportional hazards models and we further assume that the data are subject to censoring. Minimax designs are then found explicitly based on criteria corresponding...

Model-Robust Factorial Designs

Robust Hybrid Designs for Real - Time Simulation Trials

Real time simulation trials involve people and are particularly subject to a number of natural constraints imposed by standard work patterns as well as to the vagaries of the availability of individuals and unscheduled upsets. They also typically involve many factors. Well thought-out simulation experimental design is therefore especially important if the resulting overall trial is to be effici...

Optimal designs for trials with discrete time survival endpoints

In studies on event occurrence the main question is whether and when a certain event occurs. Examples of events are smoking initiation, premature termination of therapy and recovery from some disease. The timing of such events cannot always be measured very precisely and coarse time intervals are used instead. At the end of each interval the occurrence of the event is measured, until and includ...

Model-robust designs for split-plot experiments

Split-plot experiments are appropriate when some factors are more difficult and/or expensive to change than others. They require two levels of randomization resulting in a non-independent error structure. The design of such experiments has garnered much recent attention, including work on exact D-optimal split-plot designs. However, many of these procedures rely on the a priori assumption that ...