Bayesian biostatistics.

Bayesian biostatistics. Emmanuel Lesaffre, Andrew B. Lawson.

West Sussex: John Wiley, 2012. Octavo, laminated boards, tables, graphs.

Having experienced phenomenal growth in recent years, biostatistics has undergone considerable technical innovation in both methodology and computational practicality. One area that has experienced the most 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. Supported by an accompanying website hosting free software and case study guides. This volume introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity.

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