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:
Sera F, Armstrong B, Blangiardo M, Gasparrini A. An extended mixed-effects framework for meta-analysis. Statistics in Medicine. 2019;38(29):5429-5444. [freely available here]
The article also presents the R package mixmeta that implements the extended meta-analytical framework and used to perform the examples in of applications in the article.
The material:
- 01.StandardMA.R, 02.MultivariateMA.R, 03.MultilevelMA.R, 04.DoseResponseMA.R, and 05.LongitudinalMA.R illustrate the general extended framework in specific meta-analytical applications, consistently with the sections in the published article
- 06a.simul.r and 06b.simul_parallel.csv reproduce the results of the simulation study, using simple loops and the parallelized version, respectively.
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