get_basepars

Evaluate baseline time-to-event distribution parameters given covariate values in a flexsurvmix 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

get_basepars function

<dl><dt>x</dt>
<dd>Fitted model object</dd>
<dt>newdata</dt>
<dd>Data frame of alternative covariate values</dd>
<dt>event</dt>
<dd>Event</dd></dl>

Arguments

Evaluate baseline time-to-event distribution parameters given covariate values in a flexsurvmix model — get_basepars

<dl>

<dt>x</dt>
<dd>Fitted model object</dd>


<dt>newdata</dt>
<dd>Data frame of alternative covariate values</dd>


<dt>event</dt>
<dd>Event</dd>

</dl>

get_basepars: Evaluate baseline time-to-event distribution parameters given covariate values in a flexsurvmix model

Description

Usage

Arguments