Advancing spatial analysis methodologies using a bayesian approach: combining individual and aggregated data in small area studies

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The proposed research is important to all disciplines that use spatial data because it will develop new and improved methodologies for analyzing spatial data, and thus make effective use of spatial data that have been collected routinely across disciplines. Research that applies spatial analysis has increased remarkably in many disciplines as more geographically-referenced data are becoming available. Traditional spatial analysis adopts a frequentist statistical approach, which has the limitation of inability to fit complex spatial models. One important development of spatial analysis in recent years is to use a Bayesian statistical approach to analyze spatial data, referred to a Bayesian Spatial Analysis (BSA). Research has shed lights on the capability of this new approach in fitting more complex spatial models to tackle traditional problems of spatial analysis including missing data, data uncertainty, measurement errors, spatial dependence, and data integration. Compared to the UK and US, BSA is rarely used in Canada. The long term goal of our proposed research is to advance methodologies of BSA to improve our ability to analyze geographic data reliably, provide BSA training to students, promote the applications of BSA, and improve the overall standard of geographic research in Canada. Our short term goal is to develop BSA methodologies that would enable the integration of geographically-referenced individual and aggregated data in small-area research to improve the reliability of geographic studies. We will focus on developing methods for research in the fields of public health and crime, which are currently most in need of improved spatial methodologies for understanding geographic variation of disease/crime outcomes. Our research findings will be shared with two regions of public health and police in Ontario who have expressed interests in and agreed to provide data for our research. However, the BSA methodologies developed will be applicable not only in public health and crime, but also in environmental science and other applied science research.