metagam: Meta-Analysis of Generalized Additive Models

Meta-analysis of generalized additive models and generalized additive mixed models. A typical use case is when data cannot be shared across locations, and an overall meta-analytic fit is sought. 'metagam' provides functionality for removing individual participant data from models computed using the 'mgcv' and 'gamm4' packages such that the model objects can be shared without exposing individual data. Furthermore, methods for meta-analysing these fits are provided. The implemented methods are described in Sorensen et al. (2020), <doi:10.1016/j.neuroimage.2020.117416>, extending previous works by Schwartz and Zanobetti (2000) and Crippa et al. (2018) <doi:10.6000/1929-6029.2018.07.02.1>.

Version:	0.3.1
Imports:	mgcv, ggplot2, metafor, rlang
Suggests:	roxygen2, knitr, rmarkdown, devtools, covr, testthat (≥ 2.1.0)
Published:	2021-11-14
Author:	Oystein Sorensen [aut, cre], Andreas M. Brandmaier [aut], Athanasia Mo Mowinckel [aut]
Maintainer:	Oystein Sorensen <oystein.sorensen at psykologi.uio.no>
BugReports:	https://github.com/Lifebrain/metagam/issues
License:	GPL-3
URL:	https://lifebrain.github.io/metagam/, https://github.com/Lifebrain/metagam
NeedsCompilation:	no
Citation:	metagam citation info
Materials:	README
In views:	MetaAnalysis
CRAN checks:	metagam results

Documentation:

Reference manual:	metagam.pdf
Vignettes:	Dominance Plots Heterogeneity Plots Introduction Multivariate Smooth Terms Simultaneous confidence intervals and p-values

Downloads:

Package source:	metagam_0.3.1.tar.gz
Windows binaries:	r-devel: metagam_0.3.1.zip, r-release: metagam_0.3.1.zip, r-oldrel: metagam_0.3.1.zip
macOS binaries:	r-release (arm64): metagam_0.3.1.tgz, r-oldrel (arm64): metagam_0.3.1.tgz, r-release (x86_64): metagam_0.3.1.tgz, r-oldrel (x86_64): metagam_0.3.1.tgz
Old sources:	metagam archive

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