simAalenFrailty

Simulate observations from Aalen Frailty model with Gamma
distributed frailty and constant intensity.

Implementation of various statistical models for multivariate
event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate
cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random
effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>.
Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray,
Ghosh-Lin, Binomial regression) with fast computation of influence functions.

Klaus Holst

mets

Analysis of Multivariate Event Times

Klaus K. Holst

Thomas Scheike 

simAalenFrailty function

<dl><dt>n</dt>
<dd>Number of observations in each cluster</dd>
<dt>theta</dt>
<dd>Dependence paramter (variance of frailty)</dd>
<dt>K</dt>
<dd>Number of clusters</dd>
<dt>beta0</dt>
<dd>Baseline (intercept)</dd>
<dt>beta</dt>
<dd>Effect (log hazard ratio) of covariate</dd>
<dt>cens</dt>
<dd>Censoring rate</dd>
<dt>cuts</dt>
<dd>time cuts</dd>
<dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

Author

Simulate from the Aalen Frailty model — simAalenFrailty

<dl>

<dt>n</dt>
<dd>Number of observations in each cluster</dd>


<dt>theta</dt>
<dd>Dependence paramter (variance of frailty)</dd>


<dt>K</dt>
<dd>Number of clusters</dd>


<dt>beta0</dt>
<dd>Baseline (intercept)</dd>


<dt>beta</dt>
<dd>Effect (log hazard ratio) of covariate</dd>


<dt>cens</dt>
<dd>Censoring rate</dd>


<dt>cuts</dt>
<dd>time cuts</dd>


<dt>...</dt>
<dd>Additional arguments</dd>

</dl>

simAalenFrailty: Simulate from the Aalen Frailty model

Description

Usage

Arguments

Author