國家衛生研究院 NHRI:Item 3990099045/15597
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/15597


    Title: Iterative estimating equations for disease mapping with spatial zero-inflated Poisson data
    Authors: Lin, PS;Zhu, J;Lin, FC
    Contributors: Institute of Population Health Sciences
    Abstract: Spatial epidemiology often involves the analysis of spatial count data with an unusually high proportion of zero observations. While Bayesian hierarchical models perform very well for zero-inflated data in many situations, a smooth response surface is usually required for the Bayesian methods to converge. However, for infectious disease data with excessive zeros, a Wombling issue with large spatial variation could make the Bayesian methods infeasible. To address this issue, we develop estimating equations associated with disease mapping by including over-dispersion and spatial noises in a spatial zero-inflated Poisson model. Asymptotic properties are derived for the parameter estimates. Simulations and data analysis are used to assess and illustrate the proposed method.
    Date: 2024-01-10
    Relation: Stat: Bulletin of the Wisconsin Nurses Association. 2024 Jan 10;13(1):Article number e646.
    Link to: http://dx.doi.org/10.1002/sta4.646
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=2049-1573&DestApp=IC2JCR
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85181891685
    Appears in Collections:[Pei-Sheng Lin] Periodical Articles

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