Implements a wide range of model-based dose
escalation designs, ranging from classical and modern continual
reassessment methods (CRMs) based on dose-limiting toxicity endpoints to
dual-endpoint designs taking into account a biomarker/efficacy outcome. The
focus is on Bayesian inference, making it very easy to setup a new design
with its own JAGS code. However, it is also possible to implement 3+3
designs for comparison or models with non-Bayesian estimation. The whole
package is written in a modular form in the S4 class system, making it very
flexible for adaptation to new models, escalation or stopping rules.
Version: |
0.1.6 |
Depends: |
R (≥ 3.0.0), ggplot2, graphics |
Imports: |
methods, grid, gridExtra, GenSA, mvtnorm, parallel, BayesLogit, rjags, utils, tools, MASS |
Suggests: |
ggmcmc, R2WinBUGS, Rcpp, RcppArmadillo |
Published: |
2015-12-22 |
Author: |
Daniel Sabanes Bove,
Wai Yin Yeung,
Giuseppe Palermo,
Thomas Jaki |
Maintainer: |
Daniel Sabanes Bove <sabanesd at roche.com> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
Copyright: |
F. Hoffmann-La Roche Ltd |
NeedsCompilation: |
no |
Materials: |
NEWS ChangeLog |
CRAN checks: |
crmPack results |