Package: metagam 0.4.0.9000

Oystein Sorensen

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>.

Authors:Oystein Sorensen [aut, cre], Andreas M. Brandmaier [aut], Athanasia Mo Mowinckel [aut]

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metagam/json (API)

# Install 'metagam' in R:
install.packages('metagam', repos = c('https://lifebrain.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lifebrain/metagam/issues

Pkgdown site:https://lifebrain.github.io

On CRAN:

Conda:

5.85 score 11 stars 13 scripts 350 downloads 6 exports 34 dependencies

Last updated 9 months agofrom:60f4f988a1. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-winOKMar 06 2025
R-4.5-macOKMar 06 2025
R-4.5-linuxOKMar 06 2025
R-4.4-winOKMar 06 2025
R-4.4-macOKMar 06 2025
R-4.4-linuxOKMar 06 2025
R-4.3-winOKMar 06 2025
R-4.3-macOKMar 06 2025

Exports:getmasdmetagamplot_between_study_sdplot_dominanceplot_heterogeneitystrip_rawdata

Dependencies:clicolorspacedigestfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSmathjaxrMatrixmetadatmetaformgcvmunsellnlmenumDerivpbapplypillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Dominance Plots

Rendered fromdominance.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2022-01-14
Started: 2020-01-30

Heterogeneity Plots

Rendered fromheterogeneity.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2022-01-14
Started: 2020-01-30

Introduction

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2022-01-18
Started: 2020-01-30

Multivariate Smooth Terms

Rendered frommultivariate.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2022-01-14
Started: 2020-02-05

Simultaneous confidence intervals and p-values

Rendered frompvals.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2022-01-16
Started: 2021-11-12