A Scan Statistic for Continuous Data Based on the Normal Probability Model

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A Scan Statistic for Continuous Data Based on the Normal Probability Model

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Title: A Scan Statistic for Continuous Data Based on the Normal Probability Model
Author: Konty, Kevin; Kulldorff, Martin; Huang, Lan

Note: Order does not necessarily reflect citation order of authors.

Citation: Kulldorff, Martin, Lan Huang, and Kevin Konty. 2009. A scan statistic for continuous data based on the normal probability model. International Journal of Health Geographics 8:58.
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Abstract: Temporal, spatial and space-time scan statistics are commonly used to detect and evaluate the statistical significance of temporal and/or geographical disease clusters, without any prior assumptions on the location, time period or size of those clusters. Scan statistics are mostly used for count data, such as disease incidence or mortality. Sometimes there is an interest in looking for clusters with respect to a continuous variable, such as lead levels in children or low birth weight. For such continuous data, we present a scan statistic where the likelihood is calculated using the the normal probability model. It may also be used for other distributions, while still maintaining the correct alpha level. In an application of the new method, we look for geographical clusters of low birth weight in New York City.
Published Version: doi://10.1186/1476-072X-8-58
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2772848/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10230104
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