Bayesian adaptive model selection for optimizing group sequential clinical trials

Group sequential designs for clinical trials.

Bayesian Adaptive Designs for Clinical Trials

A Bayesian adaptive design is proposed for a comparative two-armed clinical trial using decision theoretical approaches. A loss function is specified to consider the cost for each patient, and the costs of making incorrect decisions at the end of a trial. At each interim analysis, the decision to terminate or to continue the trial is based on the expected loss function while concurrently incorp...

Estimation in adaptive group sequential trials

2 Group Sequential Designs (GSD) 2 2.1 GST object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1.1 Alpha spending function (SF) . . . . . . . . . . . . . . . . 4 2.2 plan.GST example . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Overall p-values for GSDs . . . . . . . . . . . . . . . . . . . . . . 6 2.3.1 Repeated p-values in a classical GSD . . . . . . . . . . . ...

Sequential Mcmc for Bayesian Model Selection

In this paper, we address the problem of sequential Bayesian model selection. This problem does not usually admit any closed-form analytical solution. We propose here an original sequential simulation-based method to solve the associated Bayesian computational problems. This method combines sequential importance sampling, a resampling procedure and reversible jump MCMC moves. We describe a gene...

Repeated confidence intervals for adaptive group sequential trials.

This paper proposes a method for computing conservative confidence intervals for a group sequential test in which an adaptive design change is made one or more times over the course of the trial. The key idea, due to Müller and Schäfer (Biometrics 2001; 57:886-891), is that by preserving the null conditional rejection probability of the remainder of the trial at the time of each adaptive change...