Bivariate Random-effects Model
The Bivariate Random-Effects Model is a statistical framework used in diagnostic test accuracy meta-analysis that belongs to the class of random-effects models and is distinguished by its joint synthesis of paired accuracy measures—typically sensitivity and specificity—while accounting for their correlation and between-study variability.
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22.1K
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799
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479
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2017–2026
65
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Bivariate Random Effects Model
305
Systematic Reviews of Diagnostic Test Accuracy
Mariska Leeflang, Jonathan J Deeks, Constantine Gatsonis et al. · Annals of Internal Medicine · 2008 · 1.1K citations · Full text
A unification of models for meta-analysis of diagnostic accuracy studies
Roger Harbord, Jonathan J Deeks, Matthias Egger et al. · Biostatistics · 2006 · 745 citations · Full text
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University of Leicester
Leicester, United Kingdom
7 h-index
20 publications
5K citations
Harvard University
Cambridge, United States
7 h-index
10 publications
443 citations
University of California, Los Angeles
Los Angeles, United States
6 h-index
9 publications
398 citations
Inserm
Paris, France
5 h-index
12 publications
684 citations
Heinrich Heine University Düsseldorf
Düsseldorf, Germany
5 h-index
8 publications
176 citations

University of Bristol
Bristol, United Kingdom
5 h-index
11 publications
3.4K citations

University of Amsterdam
Amsterdam, The Netherlands
5 h-index
9 publications
4.7K citations

National Bureau of Economic Research
Cambridge, United States
4 h-index
10 publications
456 citations
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23 publications · 1.8K citations
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Repository · 14 publications · 414 citations
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9 publications · 575 citations
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Repository · 8 publications · 354 citations
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7 publications · 346 citations
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