Clinical trial designs and analyses have generally favoured frequentist to Bayesian methods. However, Bayesian approaches are used, particularly in rare-diseases and the early trial phases, where sample sizes are generally small. For instance, when statistical models are used for dose-finding studies, Bayesian approaches are generally preferred. Two notable examples are the Continual Reassessment Method (CRM) by O’Quigley et al. (1990) and EffTox by Thall & Cook (2004). One of the perennial challenges to implementing Bayesian methods in trials has been availability of software. Both of the methods mentioned above are supported by software (discussed below) but some other examples are not. The introduction of Stan has presented a welcome opportunity for a package of Bayesian clinical trial designs, implemented with a common look-and-feel in a state-of-the-art environment for Bayesian inference. trialr aims to do exactly that. In this notebook, we walk through the CRM and EffTox designs for dose-finding implemented in Stan by trialr, and highlight some inferences that are facilitated by the posterior samples generated by rstan.

Code and data available at github.com/stan-dev/stancon_talks