crmPack2.0.0 package

Object-Oriented Implementation of Dose Escalation Designs

Package nameVersionTitleDateSizeLicense
crmPack
2.0.0
Object-Oriented Implementation of Dose Escalation DesignsSat Nov 29 20255607.95kBGPL (>= 2)
crmPack
1.0.6
Object-Oriented Implementation of CRM DesignsWed Jun 26 2024673.27kBGPL (>= 2)
crmPack
1.0.5
Object-Oriented Implementation of CRM DesignsSun Feb 04 2024707.83kBGPL (>= 2)
crmPack
1.0.4
Object-Oriented Implementation of CRM DesignsTue Jan 23 2024712.80kBGPL (>= 2)
crmPack
1.0.3
Object-Oriented Implementation of CRM DesignsFri Sep 02 20221029.09kBGPL (>= 2)
crmPack
1.0.2
Object-Oriented Implementation of CRM DesignsMon Apr 25 20221145.41kBGPL (>= 2)
crmPack
1.0.0
Object-Oriented Implementation of CRM DesignsThu Jun 13 20191708.53kBGPL (>= 2)
crmPack
0.2.9
Object-Oriented Implementation of CRM DesignsFri Dec 21 20181720.15kBGPL (>= 2)
crmPack
0.2.7
Object-Oriented Implementation of CRM DesignsTue Mar 13 20181144.82kBGPL (>= 2)
crmPack
0.2.6
Object-Oriented Implementation of CRM DesignsThu Feb 15 20181145.54kBGPL (>= 2)
crmPack
0.2.1
Object-Oriented Implementation of CRM DesignsWed May 03 20171139.89kBGPL (>= 2)
crmPack
0.2.0
Object-Oriented Implementation of CRM DesignsSat Jul 16 20161449.28kBGPL (>= 2)
crmPack
0.1.9
Object-Oriented Implementation of CRM DesignsMon Feb 29 20161435.99kBGPL (>= 2)
crmPack
0.1.8
Object-Oriented Implementation of CRM DesignsWed Feb 17 20161439.27kBGPL (>= 2)
crmPack
0.1.7
Object-Oriented Implementation of CRM DesignsTue Jan 26 20161438.78kBGPL (>= 2)
crmPack
0.1.6
Object-Oriented Implementation of CRM DesignsTue Dec 22 20151439.98kBGPL (>= 2)
crmPack
0.1.5
Object-Oriented Implementation of CRM DesignsThu Nov 12 20151439.30kBGPL (>= 2)

Implements a wide range of dose escalation designs. The focus is on model-based 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. Bayesian inference is performed via MCMC sampling in JAGS, and it is easy to setup a new design with custom 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. Further details are presented in Sabanes Bove et al. (2019) <doi:10.18637/jss.v089.i10>.

  • Maintainer: Daniel Sabanes Bove
  • License: GPL (>= 2)
  • Last published: 2025-11-29