Hossain Md Monir, Lawson Andrew B, Cai Bo, Choi Jungsoon, Liu Jihong, Kirby Russell S
Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Environ Ecol Stat. 2013 Mar 1;20(1):91-107. doi: 10.1007/s10651-012-0209-0.
We propose a space-time stick-breaking process for the disease cluster estimation. The dependencies for spatial and temporal effects are introduced by using space-time covariate dependent kernel stick-breaking processes. We compared this model with the space-time standard random effect model by checking each model's ability in terms of cluster detection of various shapes and sizes. This comparison was made for simulated data where the true risks were known. For the simulated data, we have observed that space-time stick-breaking process performs better in detecting medium- and high-risk clusters. For the real data, county specific low birth weight incidences for the state of South Carolina for the years 1997-2007, we have illustrated how the proposed model can be used to find grouping of counties of higher incidence rate.
我们提出了一种用于疾病聚集估计的时空折断棒过程。通过使用时空协变量相关的核折断棒过程来引入空间和时间效应的依赖性。我们通过检查每个模型在检测各种形状和大小的聚集方面的能力，将该模型与时空标准随机效应模型进行了比较。这种比较是针对真实风险已知的模拟数据进行的。对于模拟数据，我们观察到时空折断棒过程在检测中高风险聚集方面表现更好。对于真实数据，即南卡罗来纳州1997 - 2007年各县的低出生体重发生率，我们展示了如何使用所提出的模型来找出发病率较高的县的分组。
