simt_flexsurvmix

Simulate times to competing events from 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

simt_flexsurvmix function

<dl><dt>x</dt>
<dd>Fitted model object returned from <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>n</dt>
<dd>Number of simulations</dd></dl>

Arguments

Simulate times to competing events from a mixture multi-state model — simt_flexsurvmix

<dl>

<dt>x</dt>
<dd>Fitted model object returned from <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>n</dt>
<dd>Number of simulations</dd>

</dl>

simt_flexsurvmix: Simulate times to competing events from a mixture multi-state model

Description

Usage

Value

Arguments