Interval Estimates for Predictive Values in Diagnostic Testing with Three Outcomes
Scott Clark,Lauren Mondin,Courtney Weber,Jessica Winborn +3 more
- 01 Jan 2011
Vol. 4, pp 134-155
TL;DR: Clark et al. as discussed by the authors derived classical Wald-type and Bayesian interval estimates of positive predictive value, negative predictive value and uncertain predictive value for diagnostic tests in which the disease state remains uncertain.
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Abstract: in Diagnostic Testing with Three Outcomes Scott Clark, Lauren Mondin, Courtney Weber and Jessica Winborn Advisor: Melinda Miller Holt Abstract: In disease testing, patients and doctors are interested in estimates for positive predictive value (PPV) and negative predictive value (NPV). The PPV of a test is the probability that a patient actually has the disease, given a positive test result. The NPV is the probability that a patient actually does not have the disease, given a negative test result. Here we consider diagnostic tests in which the disease state remains uncertain, so the uncertain predictive value (UPV) is also of interest. UPV is the probability that, given an uncertain test result, follow-up testing will remain inconclusive. We derive classical Wald-type and Bayesian interval estimates of PPV, NPV, and UPV. Performance of these intervals is compared through simulation studies of interval coverage and width.
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References
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