文章基本信息

标题：CutL: an alternative to Kulldorff’s scan statistics for cluster detection with a specified cut-off level
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作者：Barbara Więckowska ; Justyna Marcinkowska
期刊名称：Geospatial Health
印刷版ISSN：1970-7096
出版年度：2017
卷号：12
期号：2
页码：217-225
DOI：10.4081/gh.2017.556
出版社：PAGEPress Publications
摘要：When searching for epidemiological clusters, an important tool can be to carry out one’s own research with the incidence rate from the literature as the reference level. Values exceeding this level may indicate the presence of a cluster in that location. This paper presents a method of searching for clusters that have significantly higher incidence rates than those specified by the investigator. The proposed method uses the classic binomial exact test for one proportion and an algorithm that joins areas with potential clusters while reducing the number of multiple comparisons needed. The sensitivity and specificity are preserved by this new method, while avoiding the Monte Carlo approach and still delivering results comparable to the commonly used Kulldorff’s scan statistics and other similar methods of localising clusters. A strong contributing factor afforded by the statistical software that makes this possible is that it allows analysis and presentation of the results cartographically.
关键词：Space clusters;Cut; off level;High incidence rate;Spatial pattern detection;Binomial test for one proportion