Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model.
Bayesian accelerated failure time model for space-time dependency in a geographically augmented survival model.
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DOI：
10.1177/0962280215596186
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发表时间：
2017-10
影响因子：
2.3
通讯作者：
Eberth JM
中科院分区：
文献类型：
--
作者：
Onicescu G;Lawson A;Zhang J;Gebregziabher M;Wallace K;Eberth JM
在本文中，我们扩展了空间显式生存模型的小面积癌症数据，允许空间和时间之间的依赖关系，并使用加速故障时间模型。在生存、密度和危险函数的定义中直接对空间依赖性进行建模。这些模型是在县级汇总数据的背景下开发的。考虑两种情况：第一种假设空间和时间分布是独立的;第二种考虑空间和时间分量之间的依赖性。我们将模型应用于路易斯安那州SEER癌症登记处的前列腺癌数据。
In this paper, we extend the spatially explicit survival model for small area cancer data by allowing dependency between space and time and using accelerated failure time models. Spatial dependency is modeled directly in the definition of the survival, density, and hazard functions. The models are developed in the context of county level aggregated data. Two cases are considered: the first assumes that the spatial and temporal distributions are independent; the second allows for dependency between the spatial and temporal components. We apply the models to prostate cancer data from the Louisiana SEER cancer registry.