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.

305

Publications

22.1K

Citations

799

Authors

479

Institutions

Publications per year

2017–2026

65

Variants

Bivariate Random Effects Model

Authors

799

  1. RD
    Richard D Riley

    Keele University, United Kingdom

    6 publications · 1K citations

    6

    h-index

  2. JJ
    Jonathan J Deeks

    University of Birmingham, United Kingdom

    4 publications · 2.2K citations

    4

    h-index

  3. AJ
    Alex J. Sutton

    University of Leicester, United Kingdom

    4 publications · 1.1K citations

    4

    h-index

  4. KR
    Keith R. Abrams

    University of Leicester, United Kingdom

    4 publications · 1K citations

    4

    h-index

  5. TS
    Theo Stijnen

    Erasmus University Rotterdam, Netherlands

    4 publications · 841 citations

    4

    h-index

1–5 of 799

Venues

  1. Statistics in Medicine

    23 publications · 1.8K citations

    20

    h-index

  2. SSRN Electronic Journal

    Repository · 14 publications · 414 citations

    12

    h-index

  3. Statistical Methods in Medical Research

    9 publications · 575 citations

    9

    h-index

  4. PubMed

    Repository · 8 publications · 354 citations

    8

    h-index

  5. Biometrics

    7 publications · 346 citations

    7

    h-index

1–5