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.
['Kwak|Minjung|M|', 'Um|Sang-Won|SW|', 'Jung|Sin-Ho|SH|']
D001699:Biometry D003198:Computer Simulation D003955:Diagnostic Tests, Routine D006801:Humans D015233:Models, Statistical D011237:Predictive Value of Tests D012680:Sensitivity and Specificity
sensitivity specificity positive predictive value negative predictive value clustered binary outcome