sim_mix_data

A synthetic dataset generated from a bimodal promotion time distribution. The available covariates are:<dl>
 <dt><code>x1</code> </dt>
<dd>continuous.</dd> <dt><code>x2</code> </dt>
<dd>factor with three levels.</dd> 
</dl>Among the 500 observations, there are 123 censoring times (<code>censoring = 0</code>) and 377 "events" (<code>censoring = 1</code>). The true status (cured or susceptible) is contained in the column <code>true_status</code> and contains 59 cured and 441 susceptible subjects.

datasets

A fully Bayesian approach in order to estimate a general family of cure rate models under the presence of covariates, see Papastamoulis and Milienos (2024) <doi:10.1007/s11749-024-00942-w> and Papastamoulis and Milienos (2024b) <doi:10.48550/arXiv.2409.10221>. The promotion time can be modelled (a) parametrically using typical distributional assumptions for time to event data (including the Weibull, Exponential, Gompertz, log-Logistic distributions), or (b) semiparametrically using finite mixtures of distributions. In both cases, user-defined families of distributions are allowed under some specific requirements. Posterior inference is carried out by constructing a Metropolis-coupled Markov chain Monte Carlo (MCMC) sampler, which combines Gibbs sampling for the latent cure indicators and Metropolis-Hastings steps with Langevin diffusion dynamics for parameter updates. The main MCMC algorithm is embedded within a parallel tempering scheme by considering heated versions of the target posterior distribution.

Panagiotis Papastamoulis

bayesCureRateModel

Bayesian Cure Rate Modeling for Time-to-Event Data

Fotios Milienos

sim_mix_data function

Format

A synthetic dataset generated from a bimodal promotion time distribution. The available covariates are:<dl>
 <dt><code>x1</code> </dt>
<dd>continuous.</dd>

 <dt><code>x2</code> </dt>
<dd>factor with three levels.</dd>

 
</dl>Among the 500 observations, there are 123 censoring times (<code>censoring = 0</code>) and 377 "events" (<code>censoring = 1</code>). The true status (cured or susceptible) is contained in the column <code>true_status</code> and contains 59 cured and 441 susceptible subjects.

sim_mix_data: Simulated dataset

Description

Usage

Arguments

Format