print.metagam

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

print.metagam function

<dl><dt>x</dt>
<dd>Object of class metagam.</dd>
<dt>...</dt>
<dd>Other arguments (not used).</dd></dl>

Arguments

Print method for metagam objects. — print.metagam

<dl>

<dt>x</dt>
<dd>Object of class metagam.</dd>


<dt>...</dt>
<dd>Other arguments (not used).</dd>

</dl>

print.metagam: Print method for metagam objects.

Description

Usage

Value

Arguments