itsadug | R Documentation |
Itsadug provides a set of functions that facilitate the evaluation,
interpretation, and visualization of GAMM models that are implemented in
the package mgcv
.
vignette('inspect', package='itsadug')
- summarizes different
functions for visualizing the model.
vignette('test', package='itsadug')
- summarizes
different functions for significance testing.
vignette('acf', package='itsadug')
- summarizes how to check
and account for autocorrelation in the residuals.
Also available online on https://www.jacolienvanrij.com.
Main functions that are provided in itsadug
for interpretation and
visualization of GAMM models:
pvisgam
plots partial interaction surfaces; it also
allows for visualizing 3-way or higher interactions.
fvisgam
plots summed interaction surfaces, with the
possibility to exclude random effects.
plot_smooth
plots 1D model estimates, and has the
possibility to exclude random effects.
plot_parametric
plot group estimates.
inspect_random
plots and optionally averages random
smooths
plot_data
plots the data
plot_topo
plots EEG topographies
compareML
Performs Chisquare test on two models
plot_diff
Calculates and visualizes the difference
between two conditions within a model
plot_diff2
Calculates and visualizes the 2 dimensional
difference between two conditions within a model
check_resid
plots four different plots to inspect the
distribution of and structure in the residuals
plot_modelfit
plots an overlay of the data and the
modelfit for randomly selected trials
diagnostics
produces plots of the distributions of
residuals and predictors in the model
acf_resid
different ways to inspect autocorrelation in
the residuals
start_event
creates an AR.start column
resid_gam
returns residuals corrected for the AR1 model
Further, there are some wrappers around the predict.gam
function to facilitate the extraction of model predictions. These can be
used for customized plots. See for an example in the vignette
'plotfunctions'
(vignette('plotfunctions', package='itsadug')
).
get_predictions
for getting the estimates for given
settings of some or all of the model predictors;
get_difference
for extracting the difference between
two conditions or two smooths or two surfaces.
get_modelterm
for extracting the smooth term (
partial) estimates.
inspect_random
and get_random
for
extracting random effects only.
Use infoMessages(FALSE)
to suppress all
information messages for the current session.
This may be helpful when creating knitr or
R markdown reports.
The vignettes are available via browseVignettes()
.
When working on a server via the command line,
using ssh -X
instead of ssh
may make the
HTML files available.
A list of all available functions is provided in
help(package='itsadug')
.
Jacolien van Rij, Martijn Wieling, R.Harald Baayen, Hedderik van Rijn
Maintainer: Jacolien van Rij (vanrij.jacolien@gmail.com)
University of Groningen, The Netherlands
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