The dfpk R package provides an interface to fit Bayesian generalized (non-)linear mixed models using Stan, which is a C++ package for obtaining Bayesian inference using the No-U-turn sampler (see http://mc-stan.org/).
dfpk package includes methods involving PK measures in the dose allocation process during a Phase I clinical trials. These methods enter PK in the dose finding designs in different ways, including covariates models, dependent variable or hierarchical models. This package provides functions to generate scenarios, and to run simulations which their objective is to determine the maximum tolerated dose (MTD).
A latest version of the package dfpk is available on CRAN and can be loaded via
install.packages("dfpk")
library(dfpk) To install the dfpk package from GitHub, first make sure that you can install the rstan package and C++ toolchain by following these instructions. The program Rtools (available on https://cran.r-project.org/bin/windows/Rtools/) comes with a C++ compiler for Windows. On OS-X, you should install Xcode. Once rstan is successfully installed, you can install dfpk from GitHub using the devtools package by executing the following in R:
if (!require(devtools)){
install.packages("devtools")
library(devtools)
}
install_github("artemis-toumazi/dfpk")If installation fails, please let us know by filing an issue.
Details on formula syntax, families and link functions, as well as prior distributions can be found on the help page of the dfpk function: {r help.dfpk, eval=FALSE} help(dfpk)
Unfortunately, fitting your model with dfpk, there is currently no way to avoid the compilation.
You can either open an issue on github or write me an email to (artemis.toumazi@gmail.com).