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.
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