Introduces 1-truncated C-vine copula mixed models to generalize GLMMs for network meta-analysis of diagnostic tests by allowing arbitrary random-effect distributions and capturing tail dependencies.
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1-truncated C-vine copula mixed models for network meta-analysis of multiple diagnostic tests
Introduces 1-truncated C-vine copula mixed models to generalize GLMMs for network meta-analysis of diagnostic tests by allowing arbitrary random-effect distributions and capturing tail dependencies.