Useful in many areas of medicine and biology, Bayesian methods are particularly attractive tools for the design of clinical trials and diagnostic tests, which are based on established information, usually from related previous studies. Advanced Bayesian Methods for Medical Test Accuracy begins with a review of the usual measures such as specificity, sensitivity, positive and negative predictive value, and the area under the ROC curve. Then the scope expands to cover the more advanced topics of verification bias, diagnostic tests with imperfect gold standards, and those for which no gold standard is available.
Promoting accuracy and efficiency of clinical trials, tests, and the diagnostic process, this book:
Enables the user to efficiently apply prior information via a WinBUGS package
Presents many ideas for the first time and goes far beyond the two standard references
Integrates reader agreement with different modalities—X-ray, CT Scanners, and more—to study their effect on medical test accuracy
Provides practical chapter-end problems
Useful for graduate students and consulting statisticians working in the various areas of diagnostic medicine and study design, this practical resource introduces the fundamentals of programming and executing BUGS, giving readers the tools and experience to successfully analyze studies for medical test accuracy.
