Generalized Scan Statistics for Disease Surveillance

Authors

  • Pei-Sheng Lin

    Corresponding author
    1. Division of Biostatistics and Bioinformatics, National Health Research Institutes
    2. Department of Mathematics, National Chung Cheng University
    • Pei-Sheng Lin, Division of Biostatistics and Bioinformatics, Institutes of Population Health, National Health Research Institutes, 35 Keyan Road, Zhunan, Miaoli 350, Taiwan.

      E-mail: pslin@nhri.org.tw

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ABSTRACT

In applying scan statistics for disease surveillance, it would be valuable to have an integrated model that simultaneously includes environmental covariates and spatial correlation. In this paper, a generalized scan statistics under quasi-likelihood functions is proposed to address this issue. We use a two-step estimation process to obtain estimates of coefficients and adapt a bootstrapping method for the minimal p-value to address the multiple-testing problem. Under suitable conditions, the proposed method is consistent and can control the type I error rate. Simulations and applications to real data sets are used to evaluate the method.

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