fmsm

Construct a multi-state model from a set of parametric survival models

Flexible parametric models for time-to-event data,
including the Royston-Parmar spline model, generalized gamma and
generalized F distributions.  Any user-defined parametric
distribution can be fitted, given at least an R function defining
the probability density or hazard. There are also tools for
fitting and predicting from fully parametric multi-state models,
based on either cause-specific hazards or mixture models.

Christopher Jackson

flexsurv

Flexible Parametric Survival and Multi-State Models

Paul Metcalfe

Jordan Amdahl

Matthew T. Warkentin

Michael Sweeting

Kevin Kunzmann

fmsm function

<dl><dt>...</dt>
<dd>Objects returned by <code>flexsurvreg</code> or
<code>flexsurvspline</code> representing fitted survival models.</dd>
<dt>trans</dt>
<dd>A matrix of integers specifying which models correspond to
which transitions. The \(r,s\) entry is <code>i</code> if the \(i\)th
argument specified in <code>...</code> is the model for the state \(r\) to
state \(s\) transition. The entry should be <code>NA</code> if the 
transition is disallowed.</dd></dl>

Arguments

Construct a multi-state model from a set of parametric survival models — fmsm

<dl>

<dt>...</dt>
<dd>Objects returned by <code>flexsurvreg</code> or
<code>flexsurvspline</code> representing fitted survival models.</dd>


<dt>trans</dt>
<dd>A matrix of integers specifying which models correspond to
which transitions. The \(r,s\) entry is <code>i</code> if the \(i\)th
argument specified in <code>...</code> is the model for the state \(r\) to
state \(s\) transition. The entry should be <code>NA</code> if the 
transition is disallowed.</dd>

</dl>

fmsm: Construct a multi-state model from a set of parametric survival models

Description

Usage

Value

Arguments