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Comparison of operational characteristics for binary tests with clustered data
Author(s) -
Kwak Minjung,
Um SangWon,
Jung SinHo
Publication year - 2015
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6485
Subject(s) - predictive value , statistics , sensitivity (control systems) , inference , diagnostic test , computer science , variance (accounting) , positive predicative value , statistical inference , binary data , statistical hypothesis testing , binary number , mathematics , artificial intelligence , medicine , emergency medicine , accounting , arithmetic , electronic engineering , engineering , business
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. Copyright © 2015 John Wiley & Sons, Ltd.