Spatial Scan Statistics for Multiple Clusters in Arbitrary Shapes

• Main Authors: Chang, Chih-Ming, 張志銘
• Other Authors: 林培生
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/2hz5pg

碩士 === 國立中正大學 === 數學系統計科學研究所 === 102 === In this study, we propose a generalized scan statistic method with quasi- likelihood function to simultaneously consider geographic clusters, covariates, and spatial correlations for detecting multiple clusters. To improve the time- consuming two-stage estimation process by Lin (2012), we first combine the Kulldorff’s scan statistic method and variogram tool to estimate spatial cor- relation, and then use the quasi-likelihood function to estimate coefficients of geographic clusters and covariates. Instead of using the traditional likeli- hood ratio test to detect cluster, we use the smallest p-value as a test statistic, and apply resampling method to address the multiple testing problem. The quasi-deviance criterion is used to regroup the estimated clusters for finding arbitrary shapes of geographic cluster. For illustration, the method is applied to enterovirus data from north Taiwan in 2003.Then we may discovery the clusters of high disease area from the analysis.