metagam-package

The main functions in the metagam package are described below.

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>.

Oystein Sorensen

metagam

Meta-Analysis of Generalized Additive Models

Andreas M. Brandmaier

Athanasia Mo Mowinckel

metagam-package function

The function <code>strip_rawdata</code> takes a
 fit produced by functions in packages <code>mgcv</code> or <code>gamm4</code> and
 removes all individual participants data.

Stripping rawdata

The function <code>metagam</code> takes a list of
 fits produced by <code>strip_rawdata</code> and computes meta-analytic
 fits.

Meta-analysis

The functions <code>plot_dominance</code> and
 <code>plot_heterogeneity</code> can be used to study the meta-analytic fit
 computed by <code>strip_rawdata</code>.

metagam-package: metagam: Meta-analysis of generalized additive models.

Description

Arguments

Stripping rawdata

Meta-analysis

Plotting