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Spatial scan statistics in loglinear models

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  • Zhang, Tonglin
  • Lin, Ge

Abstract

The likelihood ratio spatial scan statistic has been widely used in spatial disease surveillance and spatial cluster detection applications. In order to better understand cluster mechanisms, an equivalent model-based approach is proposed to the spatial scan statistic that unifies currently loosely coupled methods for including ecological covariates in the spatial scan test. In addition, the utility of the model-based approach with a Wald-based scan statistic is demonstrated to account for overdispersion and heterogeneity in background rates. Simulation and case studies show that both the likelihood ratio-based and Wald-based scan statistics are comparable with the original spatial scan statistic.

Suggested Citation

  • Zhang, Tonglin & Lin, Ge, 2009. "Spatial scan statistics in loglinear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2851-2858, June.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:8:p:2851-2858
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    References listed on IDEAS

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    1. Kulldorff, Martin & Tango, Toshiro & Park, Peter J., 2003. "Power comparisons for disease clustering tests," Computational Statistics & Data Analysis, Elsevier, vol. 42(4), pages 665-684, April.
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    1. Kunihiko Takahashi & Hideyasu Shimadzu, 2018. "Multiple-cluster detection test for purely temporal disease clustering: Integration of scan statistics and generalized linear models," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-15, November.
    2. Ge Lin & Tonglin Zhang, 2024. "Spatial monitoring to reduce COVID-19 vaccine hesitance," Journal of Geographical Systems, Springer, vol. 26(2), pages 249-264, April.
    3. Aboukhamseen, S.M. & Soltani, A.R. & Najafi, M., 2016. "Modelling cluster detection in spatial scan statistics: Formation of a spatial Poisson scanning window and an ADHD case study," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 26-31.
    4. LeSage, James & Banerjee, Sudipto & Fischer, Manfred M. & Congdon, Peter, 2009. "Spatial statistics: Methods, models & computation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2781-2785, June.
    5. Zhang, Tonglin & Lin, Ge, 2013. "On the limiting distribution of the spatial scan statistic," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 215-225.
    6. Zhang, Tonglin & Lin, Ge, 2014. "Family of power divergence spatial scan statistics," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 162-178.
    7. Liu, Ying & Liu, Yawen & Zhang, Tonglin, 2018. "Wald-based spatial scan statistics for cluster detection," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 298-310.
    8. Margherita Silan & Pietro Belloni & Giovanna Boccuzzo, 2023. "Identification of neighborhood clusters on data balanced by a poset-based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1295-1316, October.

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