Methodology

A scan statistic for continuous data based on the normal probability model

Martin Kulldorff¹ , Lan Huang² and Kevin Konty³

¹  Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA

²  National Cancer Institute, Bethesda, MD, USA; Currently at the United States Food and Drug Administration, Rockville, MD, USA

³  New York City Department of Health and Mental Hygiene, New York City, NY, USA

author email corresponding author email

International Journal of Health Geographics 2009, 8:58doi:10.1186/1476-072X-8-58

Published:	20 October 2009

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.