gg_smooth

gg_smooth.default

Given a gam model this convenience function returns a plot of all
smooth terms contained in the model. If more than one smooth is present, the
different smooth are faceted.

The Piece-wise exponential (Additive Mixed) Model
(PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a
powerful model class for the analysis of survival (or time-to-event) data,
based on Generalized Additive (Mixed) Models (GA(M)Ms).
It offers intuitive specification and robust estimation of complex survival
models with stratified baseline hazards, random effects, time-varying effects,
time-dependent covariates and cumulative effects (Bender and others (2019)),
as well as support for left-truncated data as well as competing risks,
recurrent events and multi-state settings.
pammtools provides tidy workflow for survival analysis with PAMMs,
including data simulation, transformation and other functions for data
preprocessing and model post-processing as well as visualization.

Andreas Bender

pammtools

Piece-Wise Exponential Additive Mixed Modeling Tools for
Survival Analysis

Fabian Scheipl

Johannes Piller

Philipp Kopper

Lukas Burk

gg_smooth function

<dl><dt>x</dt>
<dd>A data frame or object of class <code>ped</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>get_terms</code></dd>
<dt>fit</dt>
<dd>A model object.</dd></dl>

Arguments

Plot smooth 1d terms of gam objects — gg_smooth

<dl>

<dt>x</dt>
<dd>A data frame or object of class <code>ped</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to <code>get_terms</code></dd>


<dt>fit</dt>
<dd>A model object.</dd>

</dl>

gg_smooth: Plot smooth 1d terms of gam objects

Description

Usage

Value

Arguments

See Also

Examples