Abstract
In studies on event occurrence, the timing of events may be measured continuously using thin precise units or discretely using time periods. The design of trials with continuous-time survival endpoints has been studied for years, but very little is known about the design of trials with discrete-time survival endpoints. The optimal designs for trials where observations are recorded at discrete points in time is calculated using the generalized linear model and Weibull distribution. Applying a cost function, the optimal number of subjects and time periods are found in such a way that a sufficient power level is achieved at a minimal cost or the power level is maximized for a fixed budget. Taking the budget for a trial and the cost ratio between recruiting a new subject and obtaining a measurement per subject into account, it is observed that the cost ratio and the shape of the survival function have the greatest influence on the optimal design.
Original language | English |
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Pages (from-to) | 2086-2096 |
Number of pages | 11 |
Journal | Computational Statistics and Data Analysis |
Volume | 56 |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2012 |
Keywords
- Discrete-time longitudinal data
- Survival analysis
- Optimal design
- Cost function