{"product_id":"spatiotemporal-methods-in-environmental-epidemiology-with-r-9781032397818","title":"Spatio–Temporal Methods in Environmental Epidemiology with R","description":"\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThe book \"Spatio-Temporal Methods in Environmental Epidemiology with R\" explores the interface between environmental epidemiology and spatio-temporal modeling, linking recent developments in spatio-temporal theory with epidemiological applications. It provides clear guidelines for implementing the methodology and estimating risks, with new additions such as knowledge discovery through data, Bayesian computation, spatio-temporal analysis, and an updated chapter. The book emphasizes the importance of considering dependencies in both space and time when modeling epidemiological data and showcases the power of R, tidyverse, NIMBLE, and Stan in performing complex data analysis and modeling. \u003c\/blockquote\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 422 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 12 December 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003eSpatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, delves into the intricate interplay between environmental epidemiology and spatio-temporal modeling. It establishes a strong connection between recent advancements in spatio-temporal theory and their practical applications in epidemiology. By drawing upon real-life problems, the book showcases how recent methodological developments can effectively assess the health risks associated with environmental hazards. The clear guidelines provided within the book facilitate the implementation of the methodology and the estimation of risks in practical settings.\u003cbr\u003e\u003cbr\u003eIn the Second Edition of this text, several notable additions have been made:\u003cbr\u003e\u003cbr\u003eA comprehensive exploration of the fundamental principles underlying knowledge discovery through data has been included. A new chapter dedicated to extracting valuable information from data using R and the tidyverse has been introduced. Additional material on methods for Bayesian computation, including the utilization of NIMBLE and Stan, has been provided. New approaches for conducting spatio-temporal analysis have been introduced, along with an updated chapter covering additional topics.\u003cbr\u003e\u003cbr\u003eThroughout the book, new examples have been incorporated to enhance the understanding and application of the discussed concepts. Furthermore, the presentation of R code for examples has been expanded to provide a more comprehensive learning experience.\u003cbr\u003e\u003cbr\u003eIn addition to these enhancements, the book now features a dedicated GitHub site (https:\/\/spacetime-environ.github.io\/stepi2), which serves as a valuable resource for readers. It offers access to data, code, and further worked examples, allowing readers to delve deeper into the topics covered and explore the methodology in a hands-on manner.\u003cbr\u003e\u003cbr\u003eKey Features:\u003cbr\u003e\u003cbr\u003e• Delves into the interface between environmental epidemiology and spatio-temporal modeling\u003cbr\u003e• Incorporates examples that demonstrate the practical applications of spatio-temporal methodology in addressing societal concerns about the effects of environmental hazards on health\u003cbr\u003e• Builds a foundation upon Bayesian principles to facilitate an integrated approach to spatio-temporal modeling and environmental epidemiology\u003cbr\u003e• Discusses data analysis and various topics, including data visualization, mapping, wrangling, and analysis\u003cbr\u003e• Shows how to design networks for monitoring hazardous environmental processes and the impact of preferential sampling\u003cbr\u003e\u003cbr\u003eBy incorporating these valuable additions, Spatio-Temporal Methods in Environmental Epidemiology with R, Second Edition, remains an essential resource for researchers, practitioners, and students in the fields of environmental epidemiology and spatio-temporal modeling. It equips readers with the knowledge and tools necessary to effectively assess and manage health risks associated with environmental hazards, contributing to a more sustainable and healthier world.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1006g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 234 x 156 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032397818\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 2 ed\u003c\/p\u003e","brand":"Gavin Shaddick,James V.Zidek,Alexandra M. Schmidt","offers":[{"title":"Hardback","offer_id":44922269663482,"sku":"9781032397818","price":99.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1703267743239_book.jpg?v=1703410866","url":"https:\/\/shulphink.com\/products\/spatiotemporal-methods-in-environmental-epidemiology-with-r-9781032397818","provider":"Shulph Ink","version":"1.0","type":"link"}