Unknown

Dataset Information

0

A Bayesian Method for Cluster Detection with Application to Brain and Breast Cancer in Puget Sound.


ABSTRACT: Cluster detection is an important public health endeavor, and in this article, we describe and apply a recently developed Bayesian method. Commonly used approaches are based on so-called scan statistics and suffer from a number of difficulties, which include how to choose a level of significance and how to deal with the possibility of multiple clusters. The basis of our model is to partition the study region into a set of areas that are either "null" or "non-null," the latter corresponding to clusters (excess risk) or anticlusters (reduced risk). We demonstrate the Bayesian method and compare with a popular existing approach, using data on breast, brain, lung, prostate, and colorectal cancer, in the Puget Sound region of Washington State.

SUBMITTER: Kim AY 

PROVIDER: S-EPMC4821733 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

A Bayesian Method for Cluster Detection with Application to Brain and Breast Cancer in Puget Sound.

Kim Albert Y AY   Wakefield Jon J  

Epidemiology (Cambridge, Mass.) 20160501 3


Cluster detection is an important public health endeavor, and in this article, we describe and apply a recently developed Bayesian method. Commonly used approaches are based on so-called scan statistics and suffer from a number of difficulties, which include how to choose a level of significance and how to deal with the possibility of multiple clusters. The basis of our model is to partition the study region into a set of areas that are either "null" or "non-null," the latter corresponding to cl  ...[more]

Similar Datasets

| PRJEB21102 | ENA
| S-EPMC6211665 | biostudies-literature
| S-EPMC3769995 | biostudies-literature
| S-EPMC3483302 | biostudies-literature
| S-EPMC5825941 | biostudies-literature
| S-EPMC5811002 | biostudies-literature
| S-EPMC3186776 | biostudies-literature
| S-EPMC4824406 | biostudies-literature
| S-EPMC3196606 | biostudies-literature
| S-EPMC5395462 | biostudies-literature