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Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, this book presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process. The author presents many real-world examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.
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