stanfordheart

Heart transplant data for 82 patients from Stanford Heart Transplanation Program

datasets

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

stanfordheart function

A data frame with 82 observations on the following 4 variables.<dl class="dl-horizontal">
 <dt>survtime</dt><dd>survival time in months</dd>
 <dt>transplant</dt><dd>variable that is 1 or 0 if patient had transplant or not</dd>
 <dt>timetotransplant</dt><dd>time a transplant patient waits for operation</dd>
 <dt>state</dt><dd>variable that is 1 or 0 if time is censored or not</dd>
 </dl>

Format

Data from Stanford Heart Transplanation Program — stanfordheart

A data frame with 82 observations on the following 4 variables.<dl class='dl-horizontal'>
 <dt>survtime</dt><dd>survival time in months</dd>
 <dt>transplant</dt><dd>variable that is 1 or 0 if patient had transplant or not</dd>
 <dt>timetotransplant</dt><dd>time a transplant patient waits for operation</dd>
 <dt>state</dt><dd>variable that is 1 or 0 if time is censored or not</dd>
 </dl>

stanfordheart: Data from Stanford Heart Transplanation Program

Description

Usage

Arguments

Format