Spatio-Temporal Methods in Environmental Epidemiology
ISBN: 9780429162947
Platform/Publisher: Taylor & Francis / Chapman and Hall/CRC
Digital rights: Users: Unlimited; Printing: Unlimited; Download: Unlimited



Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and

Gavin Shaddick is a reader in statistics in the Department of Mathematical Sciences at the University of Bath. He received his master's in applied stochastic systems from University College London and his PhD in statistics and epidemiology from Imperial College London.

His research interests include the theory and application of Bayesian statistics to the areas of spatial epidemiology, environmental health risk, and the modeling of spatio-temporal fields of environmental hazards. Of particular interest are computational techniques that allow the implementation of complex statistical models to real-life applications where the scope over both space and time may be very large.

Dr. Shaddick is actively involved in a number of substantive epidemiological projects related to the effects of air pollution to health. He has worked on many large-scale funded projects, including the high-resolution mapping of environmental pollutants, the utilization of information from multiple sources in estimating exposures to environmental hazards, and the characterization of uncertainty in scenario assessment and policy support.

He is a co-author of the Oxford Handbook of Epidemiology for Clinicians , which was Highly Commended in the Basis of Medicine Category, BMA Book Awards 2013.

James V. Zidek is a professor emeritus in the Department of Statistics at the University of British Columbia. Professor Zidek received his MSc and PhD in statistics from the University of Alberta and Stanford University, respectively.

He began his research career working on Wald's statistical decision theory. That interest shifted into Bayesian decision analysis. His interest in applications also emerged early in his career and as a consultant, published with engineering collaborators, the first design code for long-span bridges, such as the famous Golden Gate Bridge in San Francisco. The combination of theory and practice

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