Comparison of operational characteristics for binary tests with clustered data.
Although statistical methodology is well-developed for comparing diagnostic tests in terms of their sensitivity and specificity, comparative inference about predictive values is not. In this paper, we consider the analysis of studies comparing operating characteristics of two diagnostic tests that are measured on all subjects and have test outcomes from multiple sites with varying number of sites among subjects. We have developed a new approach for comparing sensitivity, specificity, positive predictive value, and negative predictive value with simple variance calculation and, in particular, focus on comparing tests using difference of positive and negative predictive values. Simulation studies are conducted to show the performance of our approach. We analyze real data on patients with lung cancer, based on their diagnostic tests, to illustrate the methodology.
Duke Scholars
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Related Subject Headings
- Statistics & Probability
- Sensitivity and Specificity
- Predictive Value of Tests
- Models, Statistical
- Humans
- Diagnostic Tests, Routine
- Computer Simulation
- Biometry
- 4905 Statistics
- 4202 Epidemiology
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Statistics & Probability
- Sensitivity and Specificity
- Predictive Value of Tests
- Models, Statistical
- Humans
- Diagnostic Tests, Routine
- Computer Simulation
- Biometry
- 4905 Statistics
- 4202 Epidemiology