ppath_fmixmsm

Probability of each pathway taken through a mixture multi-state model

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

ppath_fmixmsm function

<dl><dt>x</dt>
<dd>Object returned by <code>fmixmsm</code>, representing a multi-state
model built from piecing together mixture models fitted by
<code>flexsurvmix</code>.</dd>
<dt>newdata</dt>
<dd>Data frame or list of covariate values. If omitted for a
model with covariates, a default is used, defined by all combinations of
factors if the only covariates in the model are factors, or all covariate
values of zero if there are any non-factor covariates in the model.</dd>
<dt>final</dt>
<dd>If <code>TRUE</code> then the probabilities of pathways with the same
final state are added together, to produce the probability of each
ultimate outcome or absorbing state from the multi-state model.</dd>
<dt>B</dt>
<dd>Number of simulations to use to compute 95% confidence intervals,
based on the asymptotic multivariate normal distribution of the basic
parameter estimates. If <code>B=NULL</code> then intervals are not computed.</dd></dl>

Arguments

Probability of each pathway taken through a mixture multi-state model — ppath_fmixmsm

<dl>

<dt>x</dt>
<dd>Object returned by <code>fmixmsm</code>, representing a multi-state
model built from piecing together mixture models fitted by
<code>flexsurvmix</code>.</dd>


<dt>newdata</dt>
<dd>Data frame or list of covariate values. If omitted for a
model with covariates, a default is used, defined by all combinations of
factors if the only covariates in the model are factors, or all covariate
values of zero if there are any non-factor covariates in the model.</dd>


<dt>final</dt>
<dd>If <code>TRUE</code> then the probabilities of pathways with the same
final state are added together, to produce the probability of each
ultimate outcome or absorbing state from the multi-state model.</dd>


<dt>B</dt>
<dd>Number of simulations to use to compute 95% confidence intervals,
based on the asymptotic multivariate normal distribution of the basic
parameter estimates. If <code>B=NULL</code> then intervals are not computed.</dd>

</dl>

ppath_fmixmsm: Probability of each pathway taken through a mixture multi-state model

Description

Usage

Value

Arguments