A practical guide to pre-trial simulations for Bayesian adaptive trials using SAS and BUGS

Pharmaceutical Statistics
Christian Holm HansenChristopher J Weir

Abstract

It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. Before deciding on a particular design, it is generally advisable to carry out a simulation study to characterise the properties of candidate designs under a range of plausible assumptions. The implementation of such pre-trial simulation studies presents many challenges and requires considerable statistical programming effort and time. Despite the scale and complexity, there is little existing literature to guide the implementation of such projects using commonly available software. This Teacher's Corner article provides a practical step-by-step guide to implementing such simulation studies including how to specify and fit a Bayesian model in WinBUGS or OpenBUGS using SAS, and how results from the Bayesian analysis may be pulled back into SAS and used for adaptation of allocation probabilities before simulating subsequent stages of the trial. The interface between the two software platforms is described in detail along with useful tips and tricks. A key strength of our approach is that the entire exercise can be defined and controlled from within a single SAS program.

References

May 27, 2006·Journal of Biopharmaceutical Statistics·Paul GalloUNKNOWN PhRMA Working Group
Jul 25, 2009·Statistics in Medicine·David LunnNicky Best

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Methods Mentioned

BETA
HEADLESS

Software Mentioned

SmartCache
SASAUTOS
SAS Using Gibbs Sampling ( BUGS )
. bat
Comprehensive R Archive Network
WinBUGS
modelSetRN
OpenBUGS
SAS
R

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