Sensitivity and identification quantification by a relative latent model complexity perturbation in Bayesian meta-analysis.

Roos, Malgorzata; Hunanyan, Sona; Bakka, Haakon; Rue, Håvard

Roos, Malgorzata; Hunanyan, Sona; Bakka, Haakon; Rue, Håvard.

Afiliación

Roos M; Department of Biostatistics, EBPI, University of Zurich, Zurich, Switzerland.
Hunanyan S; Department of Biostatistics, EBPI, University of Zurich, Zurich, Switzerland.
Bakka H; Department of Mathematics, University of Oslo, Oslo, Norway.
Rue H; CEMSE Division, King Abdullach University of Science and Technology, Thuwal, Saudi Arabia.

Biom J ; 63(8): 1555-1574, 2021 12.

Article en En | MEDLINE | ID: mdl-34378223

Asunto(s)

Teorema de Bayes; Incertidumbre

Palabras clave

Bayesian meta-analysis; formal sensitivity and identification diagnostics; normal-normal hierarchical model; normal-t hierarchical model; relative latent model complexity

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Teorema de Bayes Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies / Systematic_reviews Idioma: En Revista: Biom J Año: 2021 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Alemania

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