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.
