staph

This dataset originates from the Drakenstein child health study.
The data contains the following variables:<dl>
<dt>id</dt>
<dd>Randomly generated unique child ID</dd><dt>t.start</dt>
<dd>The time at which the child enters the risk set for the $k$-th event</dd><dt>t.stop</dt>
<dd>Time of $k$-th infection or censoring</dd>
.
<dt>enum</dt>
<dd>Event number. Maximum of 6.</dd><dt>hiv</dt>
<dd></dd>
</dl>

datasets

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

staph function

An object of class <code>tbl_df</code> (inherits from <code>tbl</code>, <code>data.frame</code>) with 374 rows and 6 columns.

Format

This dataset originates from the Drakenstein child health study.
The data contains the following variables:<dl>
<dt>id</dt>
<dd>Randomly generated unique child ID</dd>

<dt>t.start</dt>
<dd>The time at which the child enters the risk set for the $k$-th event</dd>

<dt>t.stop</dt>
<dd>Time of $k$-th infection or censoring</dd>
.
<dt>enum</dt>
<dd>Event number. Maximum of 6.</dd>

<dt>hiv</dt>
<dd></dd>


</dl>

staph: Time until staphylococcus aureaus infection in children, with possible recurrence

Description

Usage

Arguments

Format