survData

datasets

Algorithms to implement various Bayesian penalized survival regression models including: semiparametric proportional hazards models with lasso priors (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and three other shrinkage and group priors (Lee et al., Stat Anal Data Min, 2015 <doi:10.1002/sam.11266>); parametric accelerated failure time models with group/ordinary lasso prior (Lee et al. Comput Stat Data Anal, 2017 <doi:10.1016/j.csda.2017.02.014>).

Kyu Lee

psbcGroup

Penalized Parametric and Semiparametric Bayesian Survival Models
with Shrinkage and Grouping Priors

survData function

a data frame with 2000 observations on the following 4 variables.<dl>
 <dt><code>time</code></dt>
<dd>the time to event</dd> <dt><code>event</code></dt>
<dd>the censoring indicators for the event time; 1=event observed, 0=censored</dd> <dt><code>cluster</code></dt>
<dd>cluster numbers</dd>
 
 <dt><code>cov1</code></dt>
<dd>the first column of covariate matrix x</dd> <dt><code>cov2</code></dt>
<dd>the second column of covariate matrix x</dd> 
</dl>

Format

A simulated survival dataset. — survData

a data frame with 2000 observations on the following 4 variables.<dl>
 <dt><code>time</code></dt>
<dd>the time to event</dd>

 <dt><code>event</code></dt>
<dd>the censoring indicators for the event time; 1=event observed, 0=censored</dd>

 <dt><code>cluster</code></dt>
<dd>cluster numbers</dd>
 
 <dt><code>cov1</code></dt>
<dd>the first column of covariate matrix x</dd>

 <dt><code>cov2</code></dt>
<dd>the second column of covariate matrix x</dd>

 
</dl>

survData: A simulated survival dataset.

Description

Usage

Arguments

Format

Examples