Generalized accelerated failure time spatial frailty model for arbitrarily censored data.

ABSTRACT: Flexible incorporation of both geographical patterning and risk effects in cancer survival models is becoming increasingly important, due in part to the recent availability of large cancer registries. Most spatial survival models stochastically order survival curves from different subpopulations. However, it is common for survival curves from two subpopulations to cross in epidemiological cancer studies and thus interpretable standard survival models can not be used without some modification. Common fixes are the inclusion of time-varying regression effects in the proportional hazards model or fully nonparametric modeling, either of which destroys any easy interpretability from the fitted model. To address this issue, we develop a generalized accelerated failure time model which allows str

SUBMITTER: Zhou H 

PROVIDER: S-EPMC5352560 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature