rchazC

Piecewise constant hazard distribution

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 

rchazC function

<dl><dt>base1</dt>
<dd>baseline</dd>
<dt>rr</dt>
<dd>relative risk terms</dd>
<dt>entry</dt>
<dd>entry times for left truncation</dd></dl>

Arguments

Piecewise constant hazard distribution — rchazC

<dl>

<dt>base1</dt>
<dd>baseline</dd>


<dt>rr</dt>
<dd>relative risk terms</dd>


<dt>entry</dt>
<dd>entry times for left truncation</dd>

</dl>

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rchazC: Piecewise constant hazard distribution

Description

Usage

Arguments