Bayesian models for spatio-temporal assessment of disease

Kang, Su Yun (2014) Bayesian models for spatio-temporal assessment of disease. PhD by Publication, Queensland University of Technology.


This thesis has contributed to the advancement of knowledge in disease modelling by addressing interesting and crucial issues relevant to modelling health data over space and time. The research has led to the increased understanding of spatial scales, temporal scales, and spatial smoothing for modelling diseases, in terms of their methodology and applications. This research is of particular significance to researchers seeking to employ statistical modelling techniques over space and time in various disciplines. A broad class of statistical models are employed to assess what impact of spatial and temporal scales have on simulated and real data.

Impact and interest:

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Full-text downloads:

50 since deposited on 05 Sep 2014
44 in the past twelve months

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ID Code: 75476
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Mengersen, Kerrie, McGree, James, & Baade, Peter
Keywords: Bayesian modelling, spatio-temporal, spatial epidemiology, spatial scales, temporal scales, spatial smoothing, grid level modelling, integrated nested Laplace approximation, intrinsic Gaussian Markov random field, intrinsic conditional autoregression
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 05 Sep 2014 06:36
Last Modified: 04 Sep 2015 00:48

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