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http://dx.doi.org/10.5351/CKSS.2011.18.1.057

Multivariate Meta-Analysis Methods of Comparing the Sensitivity and Specificity of Two Diagnostic Tests  

Nam, Seon-Young (Biostatistics Division, Department of Medical Lifescience, The Catholic University of Korea)
Song, Hae-Hiang (Biostatistics Division, Department of Medical Lifescience, The Catholic University of Korea)
Publication Information
Communications for Statistical Applications and Methods / v.18, no.1, 2011 , pp. 57-69 More about this Journal
Abstract
Researchers are continuously trying to find innovative diagnostic tests and published articles are accumulating at an enormous rate in many medical fields. Meta-analysis enables previously published study results to be reviewed and summarized; therefore, an objective assessment of diagnostic tests can be done with a meta-analysis of sensitivities and specificities. Data obtained by applying two diagnostic tests to a well-defined group of diseased patients produce a pair of sensitivity and by applying the same medical tests to a group of non-diseased subjects produce a pair of specificity. The statistical tests in the meta-analysis need to consider the correlatedness of the results from two diagnostic tests applied to the same diseased and non-diseased subjects. The associations between two diagnostic test results are often found to be unequal for the diseased and non-diseased subjects. In this paper, multivariate meta-analytic methods are studied by taking into account the different associations between correlated variables. On the basis of Monte Carlo simulations, we evaluate the performance of the multivariate meta-analysis methods proposed in this paper.
Keywords
Meta analysis; diagnostic test; sensitivity and specificity; generalized linear mixed model;
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