An evaluation of computational methods for aggregate data meta-analyses of diagnostic test accuracy studies

An evaluation of computational methods for aggregate data meta-analyses of diagnostic test accuracy studies

Abstract Background A Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form likelihood function or parameter solutions, computational methods are convent...

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Bibliographic Details
Main Authors: Yixin Zhao, Bilal Khan, Zelalem F. Negeri
Format: Article
Language:English
Published: BMC 2024-05-01
Series:BMC Medical Research Methodology
Subjects:
Meta-analysis
Diagnostic test accuracy
Generalized linear mixed models
Computational methods
Adaptive Gauss-Hermite
Laplace approximation
Online Access:https://doi.org/10.1186/s12874-024-02217-2

Internet

https://doi.org/10.1186/s12874-024-02217-2

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