The Non-Parametric Identification of Generalized Accelerated Failure-Time Models
We consider a class of models that generalizes the popular Mixed Proportional Hazard (MPH) model for duration data: the Generalized Accelerated Failure-Time (GAFT) model. We show that the GAFT model is non-parametrically identified (up to a normalization). We then reconsider the non-parametric identification of the MPH model. We show that the class of MPH models is not closed under normalization. This implies that a finite mean of the mixing distribution is a necessary condition for (non-parametric) identification of the MPH model. It is impossible to test this hypothesis without imposing arbitrary restrictions on the base-line hazard and/or the regression function.
Volume (Year): 57 (1990)
Issue (Month): 2 ()
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