2012年12月
A flexible spatial scan statistic with a restricted likelihood ratio for detecting disease clusters
STATISTICS IN MEDICINE
- ,
- 巻
- 31
- 号
- 30
- 開始ページ
- 4207
- 終了ページ
- 4218
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1002/sim.5478
- 出版者・発行元
- WILEY
Spatial scan statistics are widely used tools for detection of disease clusters. Especially, the circular spatial scan statistic proposed by Kulldorff (1997) has been utilized in a wide variety of epidemiological studies and disease surveillance. However, as it cannot detect noncircular, irregularly shaped clusters, many authors have proposed different spatial scan statistics, including the elliptic version of Kulldorff's scan statistic. The flexible spatial scan statistic proposed by Tango and Takahashi (2005) has also been used for detecting irregularly shaped clusters. However, this method sets a feasible limitation of a maximum of 30 nearest neighbors for searching candidate clusters because of heavy computational load. In this paper, we show a flexible spatial scan statistic implemented with a restricted likelihood ratio proposed by Tango (2008) to (1) eliminate the limitation of 30 nearest neighbors and (2) to have surprisingly much less computational time than the original flexible spatial scan statistic. As a side effect, it is shown to be able to detect clusters with any shape reasonably well as the relative risk of the cluster becomes large via Monte Carlo simulation. We illustrate the proposed spatial scan statistic with data on mortality from cerebrovascular disease in the Tokyo Metropolitan area, Japan. Copyright (c) 2012 John Wiley & Sons, Ltd.
- リンク情報
- ID情報
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- DOI : 10.1002/sim.5478
- ISSN : 0277-6715
- eISSN : 1097-0258
- PubMed ID : 22807146
- Web of Science ID : WOS:000312451000007