Bayesian Biostatistics

Name: Bayesian Biostatistics
Brand: John Wiley & Sons Inc
SKU: 9780470018231
Price: 71.48 EUR
Availability: InStock

Автор: Emmanuel Lesaffre, Andrew B. Lawson

Език:

Корици: С твърди корици

Издател: John Wiley & Sons Inc

Наличност: Външен склад

Изпращаме след 10-18 дни

71.48 € 139.79 лв

The growth of biostatistics has been phenomenal in recent years and has been marked by considerable...

Информация за книгата

Автор

Emmanuel Lesaffre, Andrew B. Lawson

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2012

страници

534

EAN

9780470018231

ISBN

0470018232

Enbook ID

01387914

Издател

John Wiley & Sons Inc

Теглоt

1138

Размери

172 x 248 x 29

Пълно описание

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.§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.§Key Features:§Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques.§Contains introductory explanations of Bayesian principles common to all areas of application.§Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics.§Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs.§Highlights the differences between the Bayesian and classical approaches.§Supported by an accompanying website hosting free software and case study guides.§Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.

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