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.
|Author||Daniel Sabanes Bove <firstname.lastname@example.org>, Wai Yin Yeung <email@example.com>, Giuseppe Palermo <firstname.lastname@example.org>, Thomas Jaki <email@example.com>|
|Date of publication||2017-05-03 20:57:00 UTC|
|Maintainer||Daniel Sabanes Bove <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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