StatisticsHealthEconomics / multimcm

Bayesian relative mixture cure modelling with Stan.
https://StatisticsHealthEconomics.github.io/multimcm
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cure-model hierarchical-models stan

multimcm: Multilevel mixture cure modelling in Stan

Lifecycle:
experimental R-CMD-check

The goal of multimcm is to jointly model multiple event time distributions (e.g. time to disease progression (PFS) and time to death (OS)) within a Bayesian relative survival mixture cure model framework, using the Stan engine called from R.

Installation

You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("StatisticsHealthEconomics/multimcm")

Motivation

Mixture cure models are increasingly popular in health problems and in particular in oncology. A Bayesian paradigm allows the explicitly incorporation of uncertainties and principled synthesis of prior knowledge such as via expert elicitation or previous trials. By extending current methods to account for the dependence between event times we leverage additional information to make better inferences and decisions.

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.