Jon Wakefield – författare

This is a new paperback edition of the well received text Spatial Epidemiology: methods and applications. It is an easy to read, clear and concise exploration of the field of geographical variations in disease. Especially with respect to variations in environmental exposures at the small-area scale this book gives an authoritative account of current practice and developments. The recent and rapid expansion of the field looks set to continue in line with growing public, governmental and media concern about environmental and health issues, and the scientific need to understand and explain the effects of environmental pollutants on health.Of interest to epidemiologists, public health practitioners, statisticians, geographers, environmental scientists and others concerned with understanding the geographical distribution of disease and the effects of environmental exposures on human health. It will be a valuable source for undergraduate and postgraduate courses in epidemiology, medical geography, biostatistics, environmental health and environmental science as well as a useful source of reference for health policy makers, health economists, regulators and others in the field of environmental health.

Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place.The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.

Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place.The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.