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OncoBayes2 (version 0.9-4)

Bayesian Logistic Regression for Oncology Dose-Escalation Trials

Description

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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Version

Install

install.packages('OncoBayes2')

Monthly Downloads

297

Version

0.9-4

License

GPL (>= 3)

Maintainer

Sebastian Weber

Last Published

December 18th, 2025

Functions in OncoBayes2 (0.9-4)

example-combo2_trial

Two-drug combination example using BLRM Trial
.label_index

Utility function to label parameter indices according to factor levels.
example-single-agent

Single Agent Example
example-combo3

Three-drug combination example
example-combo2

Two-drug combination example
draws-OncoBayes2

Transform blrmfit or blrm_trial to draws objects
.get_X

Obtain design matrices.
.get_strata_group_fct

extracts from a blrmfit object and a given data-set the group and stratum factor
.validate_group_stratum_nesting

Test if each group is assigned to exactly 1 stratum. Error otherwise.
lodds

Logit (log-odds) and inverse-logit function.
drug_info_combo2

Dataset: drug information for a dual-agent combination study
posterior_interval.blrmfit

Posterior intervals
plot_blrm

Plot a fitted model
update.blrmfit

Update data of a BLRM analysis
hist_combo2

Dataset: historical data on two single-agents to inform a combination study
hist_combo3

Dataset: historical and concurrent data on a three-way combination
summary.blrmfit

Summarise model results
update.blrm_trial

Update data and/or prior of a BLRM trial
log_inv_logit

Numerically stable summation of log inv logit
example_model

Runs example models
hist_SA

Single-agent example
predictive_interval.blrmfit

Posterior predictive intervals
pp_data

Internal function to simulate from the posterior new parameter draws
prior_summary.blrmfit

Summarise model prior
summary.blrm_trial

Summarise trial
nsamples.blrmfit

Return the number of posterior samples
log_mean_exp

Numerically stable mean of logs
posterior_linpred.blrmfit

Posterior of linear predictor
posterior_predict.blrmfit

Posterior of predictive
codata_combo2

Dataset: historical and concurrent data on a two-way combination
blrm_trial

Dose-Escalation Trials guided by Bayesian Logistic Regression Model
blrm_formula_saturating

Build a BLRM formula with saturating interaction term in logit-space
blrm_formula_linear

Build a BLRM formula with linear interaction term in logit-space
bind_rows_0

Bind rows of multiple data frames with zero fill
diagnostic-quantities

Extract Diagnostic Quantities of OncoBayes2 Models
blrm_exnex

Bayesian Logistic Regression Model for N-compounds with EXNEX
OncoBayes2

OncoBayes2
critical_quantile

Critical quantile
dose_info_combo2

Dataset: trial dose information for a dual-agent combination study