summary.survstan

Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time models, proportional hazards models, proportional odds models, accelerated hazard models, Yang and Prentice models, and extended hazard models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.

Fabio Demarqui

survstan

Fitting Survival Regression Models via 'Stan'

Andrew Johnson

summary.survstan function

<dl><dt>object</dt>
<dd>the result of a call to summary.survstan</dd>
<dt>conf.level</dt>
<dd>the confidence level required.</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Summary for a survstan object — summary.survstan

<dl>

<dt>object</dt>
<dd>the result of a call to summary.survstan</dd>


<dt>conf.level</dt>
<dd>the confidence level required.</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

summary.survstan: Summary for a survstan object

Description

Usage

Value

Arguments