Hierarchical Models In Environmental Science.pdf
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I have always been interested in health studies. My own work has been focused on the use of Bayesian approaches to health studies. In particular I have been involved in the meta-analysis of the health effects of traffic-related air pollution in the UK48,49, and I was the lead statistician involved in the development and application of Bayesian methods to estimate the relative risk of cancer with exposure to the agricultural fungicide thiram in Poland50, and is in the process of carrying out a large systematic review of all available research on the health effects of diet. I have also published on the use of Bayesian methods to improve the estimation of the reduction in HIV transmission from pre-exposure prophylaxis51 and Bayesian approaches to the analysis of studies in substance use. In addition I have worked closely with a number of my PhD students in the development and application of Bayesian methods to health studies, especially in the analysis of health-related studies and meta-analyses. I am also interested in the use of Bayesian methods in the development of environmental management strategies, especially for air pollution and climate change, and am a member of the International Panel on Climate Change. I have also been involved in the development of the Bayes Enviro Database52, which is a database containing all the available information on environmental studies, and is able to evaluate the external validity of environmental studies. In addition I was involved in the development of the first hierarchical Bayesian model for environmental studies, and this has been used in a number of subsequent studies of air pollution and climate change and in studies investigating the health effects of traffic-related air pollution and fine particulate matter, including, for example, work on the health effects of particulate matter in children in Nepal. In addition I am interested in some of the development and application of Bayesian methods to the analysis of incomplete longitudinal data.
Finally, I would like to acknowledge the generous support I have received over the years from a number of institutions that have been, and will continue to be, an important part of my career. First, I would like to thank the University of Warwick for the award of a PhD studentship and the financial support for my first two years as a doctoral student. The award of this scholarship provided me with the opportunity to develop my skills as an environmental scientist and, in the process, I have been fortunate to have the support of a number of very helpful and supportive people from the Biology Department at the University of Warwick.
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