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Estimation of sensitivity and specificity of multiple repeated binary tests without a gold standard
Author(s) -
Wang Chunling,
Hanson Timothy E.
Publication year - 2019
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.8114
Subject(s) - gold standard (test) , markov chain monte carlo , inference , computer science , sensitivity (control systems) , binary data , statistics , monte carlo method , binary number , algorithm , mathematics , artificial intelligence , arithmetic , electronic engineering , engineering
A model for multiple diagnostic tests, applied repeatedly over time on each subject, is proposed; gold standard data are not required. The model is identifiable with as few as three tests, and correlation among tests at each time point in the diseased and nondiseased populations, as well as across time points, is explicitly included. An efficient Markov chain Monte Carlo scheme allows for straightforward posterior inference; sample R code is available in the Supporting Web Materials for this paper. The proposed model is broadly illustrated via simulations and an analysis of scaphoid fracture data from a prospective study. In addition, omnibus tests constructed from individual tests in parallel and serial are considered.