get_term

Extract partial effects for specified model terms

internal

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

get_term function

<dl><dt>data</dt>
<dd>A data frame containing variables used to fit the model. Only
first row will be used.</dd>
<dt>fit</dt>
<dd>A fitted object of class <code><a href="/link/gam?package=pammtools&version=0.7.3" data-mini-rdoc="pammtools::gam">gam</a></code>.</dd>
<dt>term</dt>
<dd>The (non-linear) model term of interest.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>seq_range</code>.</dd></dl>

Arguments

Extract partial effects for specified model terms — get_term

<dl>

<dt>data</dt>
<dd>A data frame containing variables used to fit the model. Only
first row will be used.</dd>


<dt>fit</dt>
<dd>A fitted object of class <code><a href='https://rdrr.io/pkg/mgcv/man/gam.html'>gam</a></code>.</dd>


<dt>term</dt>
<dd>The (non-linear) model term of interest.</dd>


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

</dl>

get_term: Extract partial effects for specified model terms

Description

Usage

Arguments