Bayesian Thinking in Biostatistics av Gary L (Johns Hopkins University Baltimore Maryland USA) Rosner, Purushottam W. (Medical College of Wisconsin Mi

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<P>Praise for <I>Bayesian Thinking in Biostatistics:</P><P>"This thoroughly modern Bayesian book ¿is a ''must have'' as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of illuminating applications. These are activated by excellent coverage of computing methods and provision of code. Their content on model assessment, robustness, data-analytic approaches and predictive assessments¿are essential to valid practice. The numerous exercises and professional advice make the book ideal as a text for an intermediate-level course¿" </P><P></I>-<STRONG>Thomas Louis</STRONG>, Johns Hopkins University</P><I><P>"The book introduces all the important topics that one would usually cover in a beginning graduate level class on Bayesian biostatistics. The careful introduction of the Bayesian viewpoint and the mechanics of implementing Bayesian inference in the early chapters