Böcker av Lyle D. (Broemeling and Associates Inc. Broemeling

After a review of the usual measures, including specificity, sensitivity, positive predictive value, negative predictive value, and the area under the ROC curve, this book expands its scope to cover the more advanced topics of verification bias, diagnostic tests with imperfect gold standards, and medical tests where no gold standard is available

Written by a biostatistics expert with over 20 years of experience in the field, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors. With many examples and end-of-chapter exerc

This practical book presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for analyzing repeated measures in various scientific areas, especially biostatistics. The author bases all the computing and analysis on the WinBUGS package, which provides readers with a platform that efficiently uses prior information. The book includes the WinBUGS code needed to implement posterior analysis and offers the code for download online.

This practical book presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for analyzing repeated measures in various scientific areas, especially biostatistics. The author bases all the computing and analysis on the WinBUGS package, which provides readers with a platform that efficiently uses prior information. The book includes the WinBUGS code needed to implement posterior analysis and offers the code for download online.

After a review of the usual measures, including specificity, sensitivity, positive predictive value, negative predictive value, and the area under the ROC curve, this book expands its scope to cover the more advanced topics of verification bias, diagnostic tests with imperfect gold standards, and medical tests where no gold standard is available. The author offers a practical treatment by including R and WinBUGS code in the examples and by employing the Bayesian approach throughout the text. He also provides practical problems at the end of each chapter.