03891cam a2200541Ii 45000010014000000030008000140050017000220060019000390070015000580080041000730400035001140200036001490200033001850200036002180200033002540200049002870200046003360200042003820200039004240200018004630350022004810350024005030500012005270720025005390720025005640720025005890720016006140820015006301000044006452450125006892640065008142640011008793000023008903360026009133370026009393380036009655201880010015880047028816500021029286500039029496500062029886500036030506500033030867000039031198560072031588560102032309990017033329781315118741FlBoTFG20260210180900.0m     o  d        cr cnu|||unuuu190705s2019    flu     ob    001 0 eng d  aOCoLC-PbengerdaepncOCoLC-P  a9781351645027q(electronic bk.)  a1351645021q(electronic bk.)  a9781315118741q(electronic bk.)  a1315118742q(electronic bk.)  a9781351635530q(electronic bk. : Mobipocket)  a1351635530q(electronic bk. : Mobipocket)  a9781482246421q(electronic bk. : PDF)  a1482246422q(electronic bk. : PDF)  z9781482246414  a(OCoLC)1107493672  a(OCoLC-P)1107493672 4aRA792.5 7aMATx0290002bisacsh 7aMEDx0280002bisacsh 7aREFx0000002bisacsh 7aPBT2bicssc04a614.422231 aMartínez-Beneito, Miguel A.,eauthor.10aDisease mapping :bfrom foundations to multidimensional modeling /cMiguel A. Martinez-Beneito, Paloma Botella-Rocamora. 1aBoca Raton, FL :bCRC Press, Taylor & Francis Group,c[2019] 4c©2019  a1 online resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  aDisease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period, disease, etc. Although theory will be covered, the applied component will be equally as important with lots of practical examples offered. Features: Discusses the very latest developments on multivariate and multidimensional mapping. Gives a single state-of-the-art framework that unifies most of the previously proposed disease mapping approaches. Balances epidemiological and statistical points-of-view. Requires no previous knowledge of disease mapping. Includes practical sessions at the end of each chapter with WinBUGs/INLA and real world datasets. Supplies R code for the examples in the book so that they can be reproduced by the reader. About the Authors: Miguel A. Martinez Beneito has spent his whole career working as a statistician for public health services, first at the epidemiology unit of the Valencia (Spain) regional health administration and later as a researcher at the public health division of FISABIO, a regional bio-sanitary research center. He has been also the Bayesian Hierarchical Models professor for several seasons at the University of Valencia Biostatics Master. Paloma Botella Rocamora has spent most of her professional career in academia although she now works as a statistician for the epidemiology unit of the Valencia regional health administration. Most of her research has been devoted to developing and applying disease mapping models to real data, although her work as a statistician in an epidemiology unit makes her develop and apply statistical methods to health data, in general.  aOCLC-licensed vendor bibliographic record. 0aMedical mapping. 0aEpidemiologyxStatistical methods. 7aMATHEMATICS / Probability & Statistics / General2bisacsh 7aMEDICAL / Epidemiology2bisacsh 7aREFERENCE / General2bisacsh1 aBotella-Rocamora, Paloma,eauthor.403Taylor & Francisuhttps://www.taylorfrancis.com/books/9781315118741423OCLC metadata license agreementuhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf  c93404d93403