Bayesian Biostatistics

The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets.br/br/Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials.br/br/Key Features:bulletProvides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques.bulletContains introductory explanations of Bayesian principles common to all areas of application.bulletPresents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics.bulletIllustrated throughout with examples using software including WinBUGS, OpenBUGSbold,/bold SAS and various dedicated R programs.bulletHighlights the differences between the Bayesian and classical approaches.bulletSupported by an accompanying website hosting free software and case study guides./bulletlistbr/br/Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase…