Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition

ISBN-13: 9781138575424 / Angielski / Twarda / 2018 / 464 str.

Andrew Lawson

Opis

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, the third edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications.

Spis treści

Introduction. Bayesian Inference and Modeling. Computational Issues. Residuals and Goodness-of-Fit. Disease Map Reconstruction and Relative Risk Estimation. Disease Cluster Detection. Regression and Ecological Analysis. Putative Hazard Modeling. Multiple Scale Analysis. Multivariate Disease Analysis. Spatial Survival and Longitudinal Analyses. Spatiotemporal Disease Mapping. Disease Map Surveillance. Infectious Disease Modeling. Computational Software Issues. Basic R and Win/OpenBUGS. Selected WinBUGS Code. R Code for Thematic Mapping. Appendices.

O autorze

Andrew B. Lawson is a professor of biostatistics and eminent scholar in the Division of Biostatistics and Epidemiology in the College of Medicine at the Medical University of South Carolina. He is an ASA fellow and an advisor in disease mapping and risk assessment for the World Health Organization. Dr. Lawson has published over 100 journal papers and eight books and is the founding editor of Spatial and Spatio-temporal Epidemiology. He received a PhD in spatial statistics from the University of St. Andrews. His research interests include the analysis of clustered disease maps, spatial and spatio-temporal disease surveillance, nutritional measurement error, and Bayesian latent variable and SEM modeling.