compute_cumu_diff

CIs are calculated by sampling coefficients from their posterior and
calculating the cumulative hazard difference <code>nsim</code> times. The CI
are obtained by the 2.5\

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

compute_cumu_diff function

<dl><dt>d1</dt>
<dd>A data set used as <code>newdata</code> in <code>make_X</code></dd>
<dt>d2</dt>
<dd>See <code>d1</code></dd>
<dt>model</dt>
<dd>A model object for which a predict method is implemented which
returns the design matrix (e.g., <code><a href="/link/mgcv%3A%3Agam?package=pammtools&version=0.8.1" data-mini-rdoc="pammtools::mgcv::gam">mgcv::gam</a></code>).</dd></dl>

Arguments

Calculate difference in cumulative hazards and respective standard errors — compute_cumu_diff

<dl>

<dt>d1</dt>
<dd>A data set used as <code>newdata</code> in <code>make_X</code></dd>


<dt>d2</dt>
<dd>See <code>d1</code></dd>


<dt>model</dt>
<dd>A model object for which a predict method is implemented which
returns the design matrix (e.g., <code><a href='https://rdrr.io/pkg/mgcv/man/gam.html'>mgcv::gam</a></code>).</dd>

</dl>

compute_cumu_diff: Calculate difference in cumulative hazards and respective standard errors

Description

Usage

Arguments