A self-adjusted weighted likelihood ratio test for global clustering of disease
Shu,Lianjie1; Zhou,Ruoyu1; Su,Yan2
Source PublicationJournal of Statistical Computation and Simulation
AbstractCompared to tests for localized clusters, the tests for global clustering only collect evidence for clustering throughout the study region without evaluating the statistical significance of the individual clusters. The weighted likelihood ratio (WLR) test based on the weighted sum of likelihood ratios represents an important class of tests for global clustering. Song and Kulldorff (Likelihood based tests for spatial randomness. Stat Med. 2006;25(5):825–839) developed a wide variety of weight functions with the WLR test for global clustering. However, these weight functions are often defined based on the cell population size or the geographic information such as area size and distance between cells. They do not make use of the information from the observed count, although the likelihood ratio of a potential cluster depends on both the observed count and its population size. In this paper, we develop a self-adjusted weight function to directly allocate weights onto the likelihood ratios according to their values. The power of the test was evaluated and compared with existing methods based on a benchmark data set. The comparison results favour the suggested test especially under global chain clustering models.
Keywordglobal chain clustering hot-spot clusters likelihood ratio weighted function
URLView the original
Scopus ID2-s2.0-84930327581
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Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorShu,Lianjie
Affiliation1.University of Macau,Macau,Macao
2.Department of Electromechanical Engineering,University of Macau,Macau,Macao
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Shu,Lianjie,Zhou,Ruoyu,Su,Yan. A self-adjusted weighted likelihood ratio test for global clustering of disease[J]. Journal of Statistical Computation and Simulation,2016,86(5):996-1009.
APA Shu,Lianjie,Zhou,Ruoyu,&Su,Yan.(2016).A self-adjusted weighted likelihood ratio test for global clustering of disease.Journal of Statistical Computation and Simulation,86(5),996-1009.
MLA Shu,Lianjie,et al."A self-adjusted weighted likelihood ratio test for global clustering of disease".Journal of Statistical Computation and Simulation 86.5(2016):996-1009.
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