get_event_types

Given a formula that specifies the status variable of the outcome, this function
extracts the different event types (except for censoring, specified by
<code>censor_code</code>).

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_event_types function

<dl><dt>data</dt>
<dd>Either an object inheriting from data frame or in case of
time-dependent covariates a list of data frames (of length 2), where the first data frame
contains the time-to-event information and static covariates while the second
(and potentially further data frames) contain information on time-dependent
covariates and the times at which they have been observed.</dd>
<dt>formula</dt>
<dd>A two sided formula with a <code><a href="/link/Surv?package=pammtools&version=0.7.3" data-mini-rdoc="pammtools::Surv">Surv</a></code> object
on the left-hand-side and covariate specification on the right-hand-side (RHS).
The RHS can be an extended formula, which specifies how TDCs should be transformed
using specials <code>concurrent</code> and <code>cumulative</code>. The left hand-side can
be in start-stop-notation. This, however, is only used to create left-truncated
data and does not support the full functionality.</dd>
<dt>censor_code</dt>
<dd>Specifies the value of the status variable that indicates censoring.
Often this will be <code>0</code>, which is the default.</dd></dl>

Arguments

Exctract event types — get_event_types

<dl>

<dt>data</dt>
<dd>Either an object inheriting from data frame or in case of
time-dependent covariates a list of data frames (of length 2), where the first data frame
contains the time-to-event information and static covariates while the second
(and potentially further data frames) contain information on time-dependent
covariates and the times at which they have been observed.</dd>


<dt>formula</dt>
<dd>A two sided formula with a <code><a href='https://rdrr.io/pkg/survival/man/Surv.html'>Surv</a></code> object
on the left-hand-side and covariate specification on the right-hand-side (RHS).
The RHS can be an extended formula, which specifies how TDCs should be transformed
using specials <code>concurrent</code> and <code>cumulative</code>. The left hand-side can
be in start-stop-notation. This, however, is only used to create left-truncated
data and does not support the full functionality.</dd>


<dt>censor_code</dt>
<dd>Specifies the value of the status variable that indicates censoring.
Often this will be <code>0</code>, which is the default.</dd>

</dl>

get_event_types: Exctract event types

Description

Usage

Arguments