getPCWDistr

This returns event times with a distribution resulting from piece-wise constant hazards
using the inversion method.

Based on the illness-death model a large number of clinical
trials with oncology endpoints progression-free survival (PFS) and
overall survival (OS) can be simulated, see Meller, Beyersmann and
Rufibach (2019) <doi:10.1002/sim.8295>. The simulation set-up allows
for random and event-driven censoring, an arbitrary number of
treatment arms, staggered study entry and drop-out. Exponentially,
Weibull and piecewise exponentially distributed survival times can be
generated. The correlation between PFS and OS can be calculated.

Alexandra Erdmann

simIDM

Simulating Oncology Trials using an Illness-Death Model

Kaspar Rufibach

Holger Löwe

Daniel Sabanés Bové

F. Hoffmann-La Roche AG 

University of Ulm 

getPCWDistr function

<dl><dt>U</dt>
<dd>(<code>numeric</code>) uniformly distributed random variables.</dd>
<dt>haz</dt>
<dd>(<code>numeric</code>) piecewise constant hazard.</dd>
<dt>pw</dt>
<dd>(<code>numeric</code>) time intervals for the piecewise constant hazard.</dd>
<dt>t_0</dt>
<dd>(<code>numeric</code>) the starting times.</dd></dl>

Arguments

Piecewise Exponentially Distributed Event Times — getPCWDistr

<dl>

<dt>U</dt>
<dd>(<code>numeric</code>) uniformly distributed random variables.</dd>


<dt>haz</dt>
<dd>(<code>numeric</code>) piecewise constant hazard.</dd>


<dt>pw</dt>
<dd>(<code>numeric</code>) time intervals for the piecewise constant hazard.</dd>


<dt>t_0</dt>
<dd>(<code>numeric</code>) the starting times.</dd>

</dl>

getPCWDistr: Piecewise Exponentially Distributed Event Times

Description

Usage

Value

Arguments

Examples