|Title||Comparison of operational characteristics for binary tests with clustered data.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Kwak, Minjung, Sang-Won Um, and Sin-Ho Jung|
|Date Published||2015 Jul 10|
|Keywords||Biometry, Computer Simulation, Diagnostic Tests, Routine, Humans, Models, Statistical, Predictive Value of Tests, Sensitivity and Specificity|
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.
|Alternate Journal||Stat Med|
|Original Publication||Comparison of operational characteristics for binary tests with clustered data.|
|PubMed Central ID||PMC4632652|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
P30 CA082709 / CA / NCI NIH HHS / United States
CA142538-01 / CA / NCI NIH HHS / United States
Comparison of operational characteristics for binary tests with clustered data.