gasparrini/2019_sera_StatMed_Rcode
(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".
Alternative Title
Updated R code and data from Sera Statistics in Medicine 2019
Keywords
Meta-analysis| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software R script |
| 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 | 15 Oct 2026 09:13 |
| Publisher | Github |
No files available. Please consult associated links.
