An R package for personalized treatment selection at a single decision point.
Bayesian predictive model for personalized treatment selection for new untreated patients, which leverages known predictive and prognostic biomarkers. In particular, predictive biomarkers are exploited to inform a product partition model with covariates (PPMx) to obtain homogeneous clusters.
The implementation has been done in C++ through the use of Rcpp and RcppArmadillo.
Authors: Matteo Pedone, Raffaele Argiento, Francesco Stingo
Maintainer: Matteo Pedone.
You can install the development version of treatppmx from GitHub with:
# install.packages("devtools")
devtools::install_github("mattpedone/treatppmx")NOTE that this package depends on vweights.
# install.packages("devtools")
devtools::install_github("mattpedone/vweights")It has only been tested on a PC running Ubuntu 20.04.2 LTS.