bhmbasket - Bayesian Hierarchical Models for Basket Trials
Provides functions for the evaluation of basket trial
designs with binary endpoints. Operating characteristics of a
basket trial design are assessed by simulating trial data
according to scenarios, analyzing the data with Bayesian
hierarchical models (BHMs), and assessing decision
probabilities on stratum and trial-level based on Go / No-go
decision making. The package is build for high flexibility
regarding decision rules, number of interim analyses, number of
strata, and recruitment. The BHMs proposed by Berry et al.
(2013) <doi:10.1177/1740774513497539> and Neuenschwander et al.
(2016) <doi:10.1002/pst.1730>, as well as a model that combines
both approaches are implemented. Functions are provided to
implement Bayesian decision rules as for example proposed by
Fisch et al. (2015) <doi:10.1177/2168479014533970>. In
addition, posterior point estimates (mean/median) and credible
intervals for response rates and some model parameters can be
calculated. For simulated trial data, bias and mean squared
errors of posterior point estimates for response rates can be
provided.
