An extended mixed-effects framework for meta-analysis.
Stat Med
; 38(29): 5429-5444, 2019 12 20.
Article
em En
| MEDLINE
| ID: mdl-31647135
ABSTRACT
Standard methods for meta-analysis are limited to pooling tasks in which a single effect size is estimated from a set of independent studies. However, this setting can be too restrictive for modern meta-analytical applications. In this contribution, we illustrate a general framework for meta-analysis based on linear mixed-effects models, where potentially complex patterns of effect sizes are modeled through an extended and flexible structure of fixed and random terms. This definition includes, as special cases, a variety of meta-analytical models that have been separately proposed in the literature, such as multivariate, network, multilevel, dose-response, and longitudinal meta-analysis and meta-regression. The availability of a unified framework for meta-analysis, complemented with the implementation in a freely available and fully documented software, will provide researchers with a flexible tool for addressing nonstandard pooling problems.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Metanálise como Assunto
/
Modelos Estatísticos
Tipo de estudo:
Observational_studies
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Prognostic_studies
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Risk_factors_studies
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Systematic_reviews
Limite:
Humans
Idioma:
En
Revista:
Stat Med
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Reino Unido