While mapped data provide a common ground for discussions between the public, the media, regulatory agencies, and public health researchers, the analysis of spatially referenced data has experienced a phenomenal growth over the last two decades, thanks in part to the development of geographical information systems (GISs). This is the first thorough overview to integrate spatial statistics with data management and the display capabilities of GIS. It describes methods for assessing the likelihood of observed patterns and quantifying the link between exposures and outcomes in spatially correlated data. This introductory text is designed to serve as both an introduction for the novice and a reference for practitioners in the field Requires only minimal background in public health and only some knowledge of statistics through multiple regression Touches upon some advanced topics, such as random effects, hierarchical models and spatial point processes, but does not require prior exposure Includes lavish use of figures/illustrations throughout the volume as well as analyses of several data sets (in the form of "data breaks") Exercises based on data analyses reinforce concepts
The notation we use follows mostly that of Christensen (1991), as this text most closely links geostatistics to linear model theory. Good texts on geostatistics are Chil`es and Delfiner (2012), Christensen (1991), Cressie (1993), ...
Relevant references are given whenever possible to direct researchers to the most useful writings on the subject. Unlike most compendia of this nature, the book starts out by exploring the available software for spatial analysis.
DETAILS A iterative algorithm due to M. A. Saunders (see Paige and Saunders, 1975) is used to solve the linear system. This algorithm requires the matrix products S y, for vectory. In spatial. c.g. solve this product is computed using ...
This practical guide will be essential reading for postgraduate students in infectious disease epidemiology, health protection trainees, and practicing epidemiologists.
Bayesian detection of clusters and discontinuities in disease maps. Biometrics 56, 13–21. ... Modelling disease incidence data with spatial and spatio-temporal Dirichlet process mixtures. ... Disease Mapping with WinBUGS and MLwiN.
Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,
This 4-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. 1985 edition. Includes 310 figures and 18 tables.
Schieber GJ, Gottret P, Fleisher LK, Leive AA. Financing global health: mission unaccomplished. Health Aff (Millwood) 2007;26(4):921–934. Brilliant L. 2006. Help stop the next pandemic. http://www.ted.com/index.php/talks/ ...
This volume contains 40 selected full-text contributions from the Sixth European Conference on Geostatistics for Environmental Applications, geoENV IV, held in Rhodes, Greece, October 25-26, 2006.
Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.