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This book provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementations, with an emphasis on healthcare techniques. Through examples, exercises, and both introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics. The book is split into two parts: Part 1 provides an introduction into Bayesian methodology, common to all areas of Bayesian statistics, including Posterior Sampling and Computation. Part 2 expands on these methods and examines their applications within the field of biostatistics, with chapters on Clinical Trials, Longitudinal Studies, Survival Analysis, Errors-in-Measurement Models, Disease Mapping, Cross-Sectional and Cohort Studies, Bioinformatics, and Bioassay. An accompanying website allows the reader to replay the case studies and examples of implementations, allowing for a stronger understanding of the concepts.
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This book provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementations, with an emphasis on healthcare techniques. Through examples, exercises, and both introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics. The book is split into two parts: Part 1 provides an introduction into Bayesian methodology, common to all areas of Bayesian statistics, including Posterior Sampling and Computation. Part 2 expands on these methods and examines their applications within the field of biostatistics, with chapters on Clinical Trials, Longitudinal Studies, Survival Analysis, Errors-in-Measurement Models, Disease Mapping, Cross-Sectional and Cohort Studies, Bioinformatics, and Bioassay. An accompanying website allows the reader to replay the case studies and examples of implementations, allowing for a stronger understanding of the concepts.