cifregFG

Convenience wrapper for <code>cifreg</code> that specifically fits the Fine-Gray model
by setting <code>propodds=NULL</code>. This provides subdistribution hazard ratio interpretations.

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 

cifregFG function

<dl><dt>formula</dt>
<dd>Formula with an 'Event' outcome.</dd>
<dt>data</dt>
<dd>Data frame.</dd>
<dt>propodds</dt>
<dd>Set to <code>NULL</code> to fit the Fine-Gray model (default behavior of this function).</dd>
<dt>...</dt>
<dd>Additional arguments passed to <code>cifreg</code>.</dd></dl>

Arguments

Author

Fine-Gray Cumulative Incidence Function Regression — cifregFG

<dl>

<dt>formula</dt>
<dd>Formula with an 'Event' outcome.</dd>


<dt>data</dt>
<dd>Data frame.</dd>


<dt>propodds</dt>
<dd>Set to <code>NULL</code> to fit the Fine-Gray model (default behavior of this function).</dd>


<dt>...</dt>
<dd>Additional arguments passed to <code>cifreg</code>.</dd>

</dl>

cifregFG: Fine-Gray Cumulative Incidence Function Regression

Description

Usage

Value

Arguments

Author

See Also