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A collection of refereed papers from a six-week workshop on statistics in the health sciences, that brought together theoretical and applied statisticians from universities, medical and public health schools, government and private research institutions, and pharmaceutical companies involved in prediction problems in the life and social sciences and in diagnostic and screening tests. A number of papers with applications were presented and particularly lively discussions ensued involving the critical issues and difficulties in using and interpreting diagnostic tests and implementing mass screening programs. The prediction or controlling future events, such as survival, comparative survival and survival post intervention for a disease or even for certain biological or natural events was also represented by participants who presented work that devised predictive methodology for a variety of problems mainly from a Bayesian perspective.
While this book discusses a variety of approaches to prediction, including those based on parametric, nonparametric, and non-stochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach.
A fascinating investigation into the foundations of statistical inference This publication examines the distinct philosophical foundations of different statistical modes of parametric inference.
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