  This paper presents an approach to modeling progressive event-history data
when the overall objective is prediction based on time-dependent covariates.
This approach does not model the hazard function directly. Instead, it models
the process of the state indicators of the event history so that the
time-dependent covariates can be incorporated and predictors of the future
events easily formulated. Our model can be applied to a range of real-world
problems in medical and agricultural science.
