A DDP model for survival regression
Seminar Room 1, Newton Institute
We develop a Dependent Dirichlet Process model for survival analysis data. A major feature of the proposed approach is that there is no necessity for resulting survival curve estimates to satisfy the ubiquotous proportional hazards assumption. An illustration based on a cancer clinical trial is given where survival probabilities for times early in the study are estimated to be lower for those on a high dose treatment regimen than for those on the low dose treatment, while the reverse is true later for later times, possibly due to the toxic effect of the high dose for those who are not as healthy at the beginning of the study.