D-Optimal Designs for a Continuous Predictor in Longitudinal Trials with Discrete-Time Survival Endpoints

• Activity Number: 171
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Maryam Safarkhani*+ and Mirjam Moerbeek
• Companies: and Utrecht University
• Keywords: Design region ; Optimal design point ; Optimal design weight ; Sequential construction algorithm ; Underlying survival function

Abstract

In designing an experiment with one single, continuous predictor, the questions comprise what is the optimal number of the predictor's values, what are these values and how many subjects to assign to each of these values. We study locally D-optimal designs for such experiments with discrete-time survival data by using a sequential construction algorithm. In discrete-time survival data, an event might occur at any point in time but the timing to event occurrence is only measured in discrete time intervals like years, months or weeks. Using the Weibull survival function for modeling the underlying time to event, it is shown that the optimal designs in the design regions D=[0.5,1] and D=[0.75,1] have two points which coincide with the design region's boundaries, but the design weights highly depend on the predictor effect size and its direction, the survival pattern and the number of time intervals.