Bayesian Logistic Regression for Oncology Dose-Escalation Trials

Bayesian logistic regression model with optional EXchangeability-NonEXchangeability parameter modelling for flexible borrowing from historical or concurrent data-sources. The safety model can guide dose-escalation decisions for adaptive oncology Phase I dose-escalation trials which involve an arbitrary number of drugs. Please refer to Neuenschwander et al. (2008) and Neuenschwander et al. (2016) for details on the methodology.


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install.packages("OncoBayes2")

0.5-4 by Sebastian Weber, 3 days ago


Browse source code at https://github.com/cran/OncoBayes2


Authors: Novartis Pharma AG [cph] , Sebastian Weber [aut, cre] , Andrew Bean [aut] , Lukas A. Widmer [aut] , Trustees of Columbia University [cph] (src/init.cpp , tools/make_cc.R , R/stanmodels.R , src/Makevars , src/Makevars.win)


Documentation:   PDF Manual  


GPL (>= 3) license


Imports assertthat, checkmate, Formula, rstan, rstantools, bayesplot, ggplot2, dplyr, tibble, tidyr, abind, RBesT

Depends on Rcpp, methods

Suggests rmarkdown, knitr, testthat, mvtnorm

Linking to StanHeaders, rstan, BH, Rcpp, RcppEigen

System requirements: GNU make, pandoc (>= 1.12.3), pandoc-citeproc


See at CRAN