gastric

A data set of survival times of patients with locally advanced,
nonresectable gastric carcinoma. The patients were either
treated with chemotherapy plus radiation or chemotherapy alone.

datasets

Efficient Markov chain Monte Carlo (MCMC) algorithms for fully
Bayesian estimation of dynamic survival models with shrinkage priors.
Details on the algorithms used are provided in Wagner (2011) <doi:10.1007/s11222-009-9164-5>,
Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and
Cadonna et al. (2020) <doi:10.3390/econometrics8020020>.

Daniel Winkler

shrinkDSM

Efficient Bayesian Inference for Dynamic Survival Models with
Shrinkage

Peter Knaus

gastric function

A data frame with 90 rows and 4 variables:<dl>
 <dt>id</dt>
<dd>patient id</dd> <dt>radiation</dt>
<dd>dummy variable indicating which treatment was employed,
 0 = chemotherapy, 1 = combined chemotherapy/radiation</dd> <dt>time</dt>
<dd>time survived by patient in days</dd> <dt>status</dt>
<dd>dummy variable indicating whether death of the patient was observed,
 0 = death not observed (i.e. censored), 1 = death observed.</dd>
</dl>

Format

Survival times of gastric cancer patients — gastric

A data frame with 90 rows and 4 variables:<dl>
 <dt>id</dt>
<dd>patient id</dd>

 <dt>radiation</dt>
<dd>dummy variable indicating which treatment was employed,
 0 = chemotherapy, 1 = combined chemotherapy/radiation</dd>

 <dt>time</dt>
<dd>time survived by patient in days</dd>

 <dt>status</dt>
<dd>dummy variable indicating whether death of the patient was observed,
 0 = death not observed (i.e. censored), 1 = death observed.</dd>


</dl>

gastric: Survival times of gastric cancer patients

Description

Usage

Arguments

Format