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Wald-based spatial scan statistics for cluster detection

Author

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  • Liu, Ying
  • Liu, Yawen
  • Zhang, Tonglin

Abstract

The spatial scan test, which is often carried out by maximizing a likelihood ratio-based statistic over a collection of cluster candidates, is widely used in cluster detection and disease surveillance. As the likelihood ratio statistic may not be available if the exact distribution of the response variable is not specified, a Wald-based spatial scan approach is proposed. The idea is to construct a special explanatory variable for spatial clusters in the linear function of a statistical model. The spatial scan test is carried out by scanning the special explanatory variable over the collection of cluster candidates. An advantage is that the Wald-based spatial scan statistic can bridge spatial clusters and linear functions of statistical models. It can be easily combined with well-known statistical models beyond generalized linear models. It is expected that the proposed approach will have a great impact on cluster detection when the likelihood inference is intractable or unavailable.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:csdana:v:127:y:2018:i:c:p:298-310
    DOI: 10.1016/j.csda.2018.06.002
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    References listed on IDEAS

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    1. Zhang, Tonglin & Lin, Ge, 2009. "Spatial scan statistics in loglinear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2851-2858, June.
    2. 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.
    3. Lan Huang & Martin Kulldorff & David Gregorio, 2007. "A Spatial Scan Statistic for Survival Data," Biometrics, The International Biometric Society, vol. 63(1), pages 109-118, March.
    4. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    5. Huang, Lan & Tiwari, Ram C. & Zou, Zhaohui & Kulldorff, Martin & Feuer, Eric J., 2009. "Weighted Normal Spatial Scan Statistic for Heterogeneous Population Data," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 886-898.
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    Cited by:

    1. Silva, Ivair R. & Duczmal, Luiz & Kulldorff, Martin, 2021. "Confidence intervals for spatial scan statistic," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).

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