Abstract
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.
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