gasparrini/2019_sera_StatMed_Rcode
Gasparrini, A
(2019).
gasparrini/2019_sera_StatMed_Rcode.
[Dataset].
Github.
https://github.com/gasparrini/2019_sera_StatMed_Rcode
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".
Keywords
Meta-analysisItem Type | Dataset |
---|---|
Capture method | Simulation |
Date | 11 November 2019 |
Language(s) of written materials | English |
Creator(s) |
Gasparrini, A |
LSHTM Faculty/Department | Faculty of Public Health and Policy > Dept of Public Health, Environments and Society |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 02 Jul 2021 14:07 |
Last Modified | 08 Jul 2021 12:48 |
Publisher | Github |
Explore Further
- Github (Online Data Resource)
ORCID: https://orcid.org/0000-0002-2271-3568