gasparrini/2019_sera_StatMed_Rcode

Gasparrini, AORCID logo (2019). gasparrini/2019_sera_StatMed_Rcode. [Dataset]. Github. https://github.com/gasparrini/2019_sera_StatMed_Rcode
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A general framework for meta-analysis based on linear mixed-effects models, where potentially complex patterns of effect sizes are modelled 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. This extended meta-analytical framework is illustrated in: "An extended mixed-effects framework for meta-analysis".

Alternative Title

Updated R code and data from Sera Statistics in Medicine 2019

Keywords

Meta-analysis

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