ajfit_flexsurvmix

This computes Aalen-Johansen estimates of the probability of occupying each
state at a series of times, using <code>ajfit</code>. The equivalent
estimates from the parametric model are then produced using
<code>p_flexsurvmix</code>, and concatenated with the nonparametric
estimates to form a tidy data frame. This data frame can then simply be
plotted using <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></code>.

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

ajfit_flexsurvmix function

<dl><dt>x</dt>
<dd>Fitted model returned by <code>flexsurvmix</code>.</dd>
<dt>maxt</dt>
<dd>Maximum time to produce parametric estimates for. By default
this is the maximum event time in the data, the maximum time we have
nonparametric estimates for.</dd>
<dt>startname</dt>
<dd>Label to give the state corresponding to "no event happened
yet". By default this is <code>"Start"</code>.</dd>
<dt>B</dt>
<dd>Number of simulation replications to use to calculate a confidence
interval for the parametric estimates in <code>p_flexsurvmix</code>. 
Comparable intervals for the Aalen-Johansen estimates are returned if this
is set. Otherwise if <code>B=NULL</code> then no intervals are returned.</dd></dl>

Arguments

This computes Aalen-Johansen estimates of the probability of occupying each
state at a series of times, using <code>ajfit</code>. The equivalent
estimates from the parametric model are then produced using
<code>p_flexsurvmix</code>, and concatenated with the nonparametric
estimates to form a tidy data frame. This data frame can then simply be
plotted using <code><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></code>.

Forms a tidy data frame for plotting the fit of parametric mixture
multi-state models against nonparametric estimates — ajfit_flexsurvmix

<dl>

<dt>x</dt>
<dd>Fitted model returned by <code>flexsurvmix</code>.</dd>


<dt>maxt</dt>
<dd>Maximum time to produce parametric estimates for. By default
this is the maximum event time in the data, the maximum time we have
nonparametric estimates for.</dd>


<dt>startname</dt>
<dd>Label to give the state corresponding to "no event happened
yet". By default this is <code>"Start"</code>.</dd>


<dt>B</dt>
<dd>Number of simulation replications to use to calculate a confidence
interval for the parametric estimates in <code>p_flexsurvmix</code>. 
Comparable intervals for the Aalen-Johansen estimates are returned if this
is set. Otherwise if <code>B=NULL</code> then no intervals are returned.</dd>

</dl>

ajfit_flexsurvmix: Forms a tidy data frame for plotting the fit of parametric mixture multi-state models against nonparametric estimates

Description

Usage

Arguments