Iterative Estimating Equations for Disease Mapping with Spatial Zero-inflated Poisson Data
- 2024-04-22 (Mon.), 10:30 AM
- 統計所B1演講廳;茶 會:上午10:10。
- 實體與線上視訊同步進行。
- Dr. Pei-Sheng Lin ( 林培生 研究員 )
- 國家衛生研究院群體健康科學研究所
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.
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最後更新日期:2024-04-16 10:25