Bayesian network meta-regression hierarchical models using heavy-tailed multivariate random effects with covariate-dependent variances.

Li, Hao; Lim, Daeyoung; Chen, Ming-Hui; Ibrahim, Joseph G; Kim, Sungduk; Shah, Arvind K; Lin, Jianxin

Li, Hao; Lim, Daeyoung; Chen, Ming-Hui; Ibrahim, Joseph G; Kim, Sungduk; Shah, Arvind K; Lin, Jianxin.

Afiliação

Li H; Department of Statistics, University of Connecticut, Storrs, Connecticut.
Lim D; Department of Statistics, University of Connecticut, Storrs, Connecticut.
Chen MH; Department of Statistics, University of Connecticut, Storrs, Connecticut.
Ibrahim JG; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Kim S; Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Shah AK; Merck & Co., Inc., Kenilworth, New Jersey.
Lin J; Merck & Co., Inc., Kenilworth, New Jersey.

Stat Med ; 40(15): 3582-3603, 2021 07 10.

Article em En | MEDLINE | ID: mdl-33846992

Assuntos

Teorema de Bayes; Humanos; Modelos Lineares; Cadeias de Markov; Método de Monte Carlo; Metanálise em Rede

Palavras-chave

arm-based model; collapsed Gibbs sampling; multivariate t distribution; surface under the cumulative ranking curve; triglycerides

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Teorema de Bayes Tipo de estudo: Clinical_trials / Health_economic_evaluation / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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