get_modelterm

A gam object, produced by <code><a href="/link/gam?package=itsadug&version=0.8&to=mgcv" rd-options="mgcv" data-mini-rdoc="mgcv::gam">gam</a></code> or
<code><a href="/link/bam?package=itsadug&version=0.8&to=mgcv" rd-options="mgcv" data-mini-rdoc="mgcv::bam">bam</a></code>.

model

A number, indicating the model term to be selected.

select

A named list of the values to restrict the estimates for the
random predictor terms. When NULL (default) all levels are returned.
Only relevant for complex interactions, which involve more than two
dimensions.

cond

Number of data points estimated for each random smooth.

n.grid

Logical: whether or not to return the confidence interval or
standard error around the estimates.

A number to scale the standard error. Defaults to 1.96, resulting
in 95% confidence intervals. For 99% confidence intervals use a value of
2.58.

GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package mgcv (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).

get_modelterm: Get estimated for selected model terms.

Description

Usage

Arguments

Value

See Also

Examples